Ce Work

Work Execution Command

Execute work efficiently while maintaining quality and finishing features.

Introduction

This command takes a work document (plan or specification) or a bare prompt describing the work, and executes it systematically. The focus is on shipping complete features by understanding requirements quickly, following existing patterns, and maintaining quality throughout.

Input Document

<input_document> #$ARGUMENTS </input_document>

Execution Workflow

Phase 0: Input Triage

Determine how to proceed based on what was provided in <input_document>.

Plan document (input is a file path to an existing plan or specification) → skip to Phase 1.

Bare prompt (input is a description of work, not a file path):

1. Scan the work area

• Identify files likely to change based on the prompt
• Find existing test files for those areas (search for test/spec files that import, reference, or share names with the implementation files)
• Note local patterns and conventions in the affected areas

2. Assess complexity and route

---

Phase 1: Quick Start

1. Read Plan and Clarify _(skip if arriving from Phase 0 with a bare prompt)_

• Read the work document completely
• Treat the plan as a decision artifact, not an execution script
• If the plan includes sections such as Implementation Units, Work Breakdown, Requirements (or legacy Requirements Trace), Files, Test Scenarios, or Verification, use those as the primary source material for execution
• Check for Execution note on each implementation unit — these carry the plan's execution posture signal for that unit (for example, test-first or characterization-first). Note them when creating tasks.
• Check for a Deferred to Implementation or Implementation-Time Unknowns section — these are questions the planner intentionally left for you to resolve during execution. Note them before starting so they inform your approach rather than surprising you mid-task
• Check for a Scope Boundaries section — these are explicit non-goals. Refer back to them if implementation starts pulling you toward adjacent work
• Review any references or links provided in the plan
• If the user explicitly asks for TDD, test-first, or characterization-first execution in this session, honor that request even if the plan has no Execution note
• If anything is unclear or ambiguous, ask clarifying questions now
• If clarifying questions were needed above, get user approval on the resolved answers. If no clarifications were needed, proceed without a separate approval step — plan scope is the plan's authority, not something to renegotiate
• Do not skip this - better to ask questions now than build the wrong thing
• Do not edit the plan body during execution. The plan is a decision artifact; progress lives in git commits and the task tracker. The only plan mutation during ce-work is the final status: active → completed flip at shipping (see references/shipping-workflow.md Phase 4 Step 2). Legacy plans may contain - [ ] / - [x] marks on unit headings — ignore them as state; per-unit completion is determined during execution by reading the current file state.

2. Setup Environment

First, check the current branch:

   current_branch=$(git branch --show-current)
   default_branch=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@')

   # Fallback if remote HEAD isn't set
   if [ -z "$default_branch" ]; then
     default_branch=$(git rev-parse --verify origin/main >/dev/null 2>&1 && echo "main" || echo "master")
   fi

If already on a feature branch (not the default branch):

First, check whether the branch name is meaningful — a name like feat/crowd-sniff or fix/email-validation tells future readers what the work is about. Auto-generated worktree names (e.g., worktree-jolly-beaming-raven) or other opaque names do not.

If the branch name is meaningless or auto-generated, suggest renaming it before continuing:

   git branch -m <meaningful-name>

Derive the new name from the plan title or work description (e.g., feat/crowd-sniff). Present the rename as a recommended option alongside continuing as-is.

Then ask: "Continue working on [current_branch], or create a new branch?"

• If continuing (with or without rename), proceed to step 3
• If creating new, follow Option A or B below

If on the default branch, choose how to proceed:

Option A: Create a new branch

   git pull origin [default_branch]
   git checkout -b feature-branch-name

Use a meaningful name based on the work (e.g., feat/user-authentication, fix/email-validation).

Option B: Use a worktree (recommended for parallel development)

   skill: ce-worktree
   # The skill will create a new branch from the default branch in an isolated worktree

Option C: Continue on the default branch

• Requires explicit user confirmation
• Only proceed after user explicitly says "yes, commit to [default_branch]"
• Never commit directly to the default branch without explicit permission

Recommendation: Use worktree if:

• You want to work on multiple features simultaneously
• You want to keep the default branch clean while experimenting
• You plan to switch between branches frequently

3. Create Task List _(skip if Phase 0 already built one, or if Phase 0 routed as Trivial)_

• Use the platform's task tracking tool (TaskCreate/TaskUpdate/TaskList in Claude Code, update_plan in Codex, or the equivalent on other harnesses) to break the plan into actionable tasks
• Derive tasks from the plan's implementation units, dependencies, files, test targets, and verification criteria
• When the plan defines U-IDs for Implementation Units, preserve the unit's U-ID as a prefix in the task subject (e.g., "U3: Add parser coverage"). This keeps blocker references, deferred-work notes, and final summaries anchored to the same identifier the plan uses, so progress and traceability remain unambiguous across plan edits
• Carry each unit's Execution note into the task when present
• For each unit, read the Patterns to follow field before implementing — these point to specific files or conventions to mirror
• Use each unit's Verification field as the primary "done" signal for that task
• Do not expect the plan to contain implementation code, micro-step TDD instructions, or exact shell commands
• Include dependencies between tasks
• Prioritize based on what needs to be done first
• Include testing and quality check tasks
• Keep tasks specific and completable

4. Choose Execution Strategy

After creating the task list, decide how to execute based on the plan's size and dependency structure:

Parallel Safety Check — required before choosing parallel dispatch:

1. Build a file-to-unit mapping from every candidate unit's Files: section (Create, Modify, and Test paths) 2. Check for intersection — any file path appearing in 2+ units means overlap 3. If overlap is found AND worktree isolation is unavailable: downgrade to serial subagents. Log the reason (e.g., "Units 2 and 4 share config/routes.rb — using serial dispatch"). Serial subagents still provide context-window isolation without shared-directory write races. 4. If overlap is found AND worktree isolation is available: parallel dispatch is still safe — subagents work in isolation, and the overlap surfaces as a predictable merge conflict the orchestrator handles via the post-batch flow below. Log the predicted overlap so the post-batch flow knows which merges to expect conflicts on.

Even with no file overlap, parallel subagents sharing the orchestrator's working directory face git index contention (concurrent staging/committing corrupts the index) and test interference (concurrent test runs pick up each other's in-progress changes). Worktree isolation eliminates both; the shared-directory fallback constraints below mitigate them.

Subagent isolation — give each parallel subagent its own working tree:

• Claude Code (`Agent` tool): pass isolation: "worktree" and run_in_background: true. The harness creates a per-subagent worktree under .claude/worktrees/agent-<id> on its own branch. Verify .claude/worktrees/ is gitignored before relying on this.
• Other platforms without built-in worktree isolation (e.g., Codex spawn_agent, Pi subagent): subagents share the orchestrator's directory.

Subagent dispatch uses your available subagent or task spawning mechanism. For each unit, give the subagent:

• The full plan file path (for overall context)
• The specific unit's Goal, Files, Approach, Execution note, Patterns, Test scenarios, and Verification
• Any resolved deferred questions relevant to that unit
• Instruction to check whether the unit's test scenarios cover all applicable categories (happy paths, edge cases, error paths, integration) and supplement gaps before writing tests

Shared-directory fallback constraints — apply only when worktree isolation is unavailable:

• Instruct each subagent: "Do not stage files (git add), create commits, or run the project test suite. The orchestrator handles testing, staging, and committing after all parallel units complete."
• These constraints prevent git index contention and test interference between concurrent subagents.
• With worktree isolation active, omit these constraints — subagents may stage, commit, and run their unit's tests within their own worktree branch.

Permission mode: Omit the mode parameter when dispatching subagents so the user's configured permission settings apply. Do not pass mode: "auto" — it overrides user-level settings like bypassPermissions.

After each subagent completes (serial mode): 1. Review the subagent's diff — verify changes match the unit's scope and Files: list 2. Run the relevant test suite to confirm the tree is healthy 3. If tests fail, diagnose and fix before proceeding — do not dispatch dependent units on a broken tree 4. Update the task list (do not edit the plan body — progress is carried by the commit) 5. Dispatch the next unit

After all parallel subagents in a batch complete (worktree-isolated mode): 1. Wait for every subagent in the current parallel batch to finish. 2. For each completed subagent, in dependency order: review the worktree's diff against the orchestrator's branch. If the subagent did not commit its own work, stage and commit it inside that worktree. 3. Merge each subagent's branch into the orchestrator's branch sequentially in dependency order. If a merge conflict surfaces, abort the merge (`git merge --abort`) and re-dispatch the conflicting unit serially against the now-merged tree — hand-resolving silently picks a side and discards one unit's intent. (Predicted overlap from the Parallel Safety Check surfaces here as a conflict, not as silent data loss in shared-directory mode.) 4. After each merge, run the relevant test suite. If tests fail, diagnose and fix before merging the next branch. 5. Update the task list (progress is carried by the merge commits). 6. After merging, remove each subagent's worktree and delete its branch. Use the absolute path and branch name returned in the subagent's result.

• Unlock the worktree first — the harness locks per-subagent worktrees: git worktree unlock <absolute-path>
• Remove the worktree: git worktree remove <absolute-path>
• Delete the branch: git branch -d <branch-name> (the branch outlives the worktree by default and accumulates as orphans if not cleaned up; -d lowercase refuses to delete unmerged branches, which is the safety we want — if it fails, investigate before forcing)

7. Dispatch the next batch of independent units, or the next dependent unit.

After all parallel subagents in a batch complete (shared-directory fallback): 1. Wait for every subagent in the current parallel batch to finish before acting on any of their results 2. Cross-check for discovered file collisions: compare the actual files modified by all subagents in the batch (not just their declared Files: lists). Subagents may create or modify files not anticipated during planning — this is expected, since plans describe what not how. A collision only matters when 2+ subagents in the same batch modified the same file. In a shared working directory, only the last writer's version survives — the other unit's changes to that file are lost. If a collision is detected: commit all non-colliding files from all units first, then re-run the affected units serially for the shared file so each builds on the other's committed work 3. For each completed unit, in dependency order: review the diff, run the relevant test suite, stage only that unit's files, and commit with a conventional message derived from the unit's Goal 4. If tests fail after committing a unit's changes, diagnose and fix before committing the next unit 5. Update the task list (do not edit the plan body — progress is carried by the commits just made) 6. Dispatch the next batch of independent units, or the next dependent unit

Phase 2: Execute

1. Task Execution Loop

For each task in priority order:

   while (tasks remain):
     - Mark task as in-progress
     - Read any referenced files from the plan or discovered during Phase 0
     - **If the unit's work is already present and matches the plan's intent** (files exist with the expected capability, or the unit's `Verification` criteria are already satisfied by the current code), the work has likely shipped on a prior branch or session. Verify it matches, mark the task complete, and move on. Do not silently reimplement.
     - Look for similar patterns in codebase
     - Find existing test files for implementation files being changed (Test Discovery — see below)
     - Implement following existing conventions
     - Add, update, or remove tests to match implementation changes (see Test Discovery below)
     - Run System-Wide Test Check (see below)
     - Run tests after changes
     - Assess testing coverage: did this task change behavior? If yes, were tests written or updated? If no tests were added, is the justification deliberate (e.g., pure config, no behavioral change)?
     - Mark task as completed
     - Evaluate for incremental commit (see below)

When a unit carries an Execution note, honor it. For test-first units, write the failing test before implementation for that unit. For characterization-first units, capture existing behavior before changing it. For units without an Execution note, proceed pragmatically.

Guardrails for execution posture:

• Do not write the test and implementation in the same step when working test-first
• Do not skip verifying that a new test fails before implementing the fix or feature
• Do not over-implement beyond the current behavior slice when working test-first
• Skip test-first discipline for trivial renames, pure configuration, and pure styling work

Test Discovery — Before implementing changes to a file, find its existing test files (search for test/spec files that import, reference, or share naming patterns with the implementation file). When a plan specifies test scenarios or test files, start there, then check for additional test coverage the plan may not have enumerated. Changes to implementation files should be accompanied by corresponding test updates — new tests for new behavior, modified tests for changed behavior, removed or updated tests for deleted behavior.

Test Scenario Completeness — Before writing tests for a feature-bearing unit, check whether the plan's Test scenarios cover all categories that apply to this unit. If a category is missing or scenarios are vague (e.g., "validates correctly" without naming inputs and expected outcomes), supplement from the unit's own context before writing tests:

System-Wide Test Check — Before marking a task done, pause and ask:

When to skip: Leaf-node changes with no callbacks, no state persistence, no parallel interfaces. If the change is purely additive (new helper method, new view partial), the check takes 10 seconds and the answer is "nothing fires, skip."

When this matters most: Any change that touches models with callbacks, error handling with fallback/retry, or functionality exposed through multiple interfaces.

2. Incremental Commits

After completing each task, evaluate whether to create an incremental commit:

Heuristic: "Can I write a commit message that describes a complete, valuable change? If yes, commit. If the message would be 'WIP' or 'partial X', wait."

If the plan has Implementation Units, use them as a starting guide for commit boundaries — but adapt based on what you find during implementation. A unit might need multiple commits if it's larger than expected, or small related units might land together. Use each unit's Goal to inform the commit message.

Commit workflow:

   # 1. Verify tests pass (use project's test command)
   # Examples: bin/rails test, npm test, pytest, go test, etc.

   # 2. Stage only files related to this logical unit (not `git add .`)
   git add <files related to this logical unit>

   # 3. Commit with conventional message
   git commit -m "feat(scope): description of this unit"

Handling merge conflicts: If conflicts arise during rebasing or merging, resolve them immediately. Incremental commits make conflict resolution easier since each commit is small and focused.

Note: Incremental commits use clean conventional messages without attribution footers. The final Phase 4 commit/PR includes the full attribution.

Parallel subagent mode: Commit ownership is split by isolation mode (see Phase 1 Step 4):

• Worktree-isolated: subagents may stage and commit inside their own worktree branch; the orchestrator merges those branches in dependency order after the batch.
• Shared-directory fallback: subagents do not commit; the orchestrator stages and commits each unit after the entire parallel batch completes.

3. Follow Existing Patterns

• The plan should reference similar code - read those files first
• Match naming conventions exactly
• Reuse existing components where possible
• Follow project coding standards (see AGENTS.md; use CLAUDE.md only if the repo still keeps a compatibility shim)
• When in doubt, grep for similar implementations

4. Test Continuously

• Run relevant tests after each significant change
• Don't wait until the end to test
• Fix failures immediately
• Add new tests for new behavior, update tests for changed behavior, remove tests for deleted behavior
• Unit tests with mocks prove logic in isolation. Integration tests with real objects prove the layers work together. If your change touches callbacks, middleware, or error handling — you need both.

5. Simplify as You Go

After completing a cluster of related implementation units (or every 2-3 units), review recently changed files for simplification opportunities — consolidate duplicated patterns, extract shared helpers, and improve code reuse and efficiency. This is especially valuable when using subagents, since each agent works with isolated context and can't see patterns emerging across units.

Don't simplify after every single unit — early patterns may look duplicated but diverge intentionally in later units. Wait for a natural phase boundary or when you notice accumulated complexity.

If a /simplify skill or equivalent is available, use it. Otherwise, review the changed files yourself for reuse and consolidation opportunities.

6. Figma Design Sync (if applicable)

For UI work with Figma designs:

• Implement components following design specs
• Use ce-figma-design-sync agent iteratively to compare
• Fix visual differences identified
• Repeat until implementation matches design

6. Track Progress

• Keep the task list updated as you complete tasks
• Note any blockers or unexpected discoveries
• Create new tasks if scope expands
• Keep user informed of major milestones
• When the plan defines U-IDs for Implementation Units, or the plan or origin document carries stable R-IDs (and optionally A/F/AE IDs), reference them in blockers, deferred-work notes, task summaries, and final verification — not routine status updates. U-IDs anchor units across plan edits; R/A/F/AE anchor product intent across the brainstorm-plan handoff. Use the IDs the plan supplies and do not invent ones it does not. This preserves traceability without burying signal under noise.

Phase 3-4: Quality Check and Finishing Work

When all Phase 2 tasks are complete and execution transitions to quality check, you must read references/shipping-workflow.md for the full shipping workflow.Do not skip this.

Key Principles

Start Fast, Execute Faster

• Get clarification once at the start, then execute
• Don't wait for perfect understanding - ask questions and move
• The goal is to finish the feature, not create perfect process

The Plan is Your Guide

• Work documents should reference similar code and patterns
• Load those references and follow them
• Don't reinvent - match what exists

Test As You Go

• Run tests after each change, not at the end
• Fix failures immediately
• Continuous testing prevents big surprises

Quality is Built In

• Follow existing patterns
• Write tests for new code
• Run linting before pushing
• Review every change — inline for simple additive work, full review for everything else

Ship Complete Features

• Mark all tasks completed before moving on
• Don't leave features 80% done
• A finished feature that ships beats a perfect feature that doesn't

Common Pitfalls to Avoid

• Analysis paralysis - Don't overthink, read the plan and execute
• Skipping clarifying questions - Ask now, not after building wrong thing
• Ignoring plan references - The plan has links for a reason
• Testing at the end - Test continuously or suffer later
• Forgetting to track progress - Update task status as you go or lose track of what's done
• 80% done syndrome - Finish the feature, don't move on early
• Skipping review - Every change gets reviewed; only the depth varies
• Re-scoping the plan into human-time phases - The plan's Implementation Units define the scope of execution. Do not estimate human-hours per unit, propose multi-day breakdowns, or ask the user to pick a subset of units for "this session". Agents execute at agent speed, and context-window pressure is addressed by subagent dispatch (Phase 1 Step 4), not by phased sessions. If a plan-file input is genuinely too large for a single execution, say so plainly and suggest the user return to /ce-plan to reduce scope — don't invent session phases as a workaround. For bare-prompt input, Phase 0's Large routing already handles oversized work

Shipping Workflow

This file contains the shipping workflow (Phase 3-4). It is loaded when all Phase 2 tasks are complete and execution transitions to quality check.

Phase 3: Quality Check

1. Run Core Quality Checks

Always run before submitting:

   # Run full test suite (use project's test command)
   # Examples: bin/rails test, npm test, pytest, go test, etc.

   # Run linting (per AGENTS.md)
   # Use linting-agent before pushing to origin

2. Simplify (Claude Code only; REQUIRED for >=30 changed lines)

Before code review, run the /simplify skill on the change to consolidate duplicated patterns, remove dead code, and improve reuse. Skip when the diff is purely mechanical (formatting, dependency bumps, lint fixes, generated artifacts) -- simplification has no useful yield on those.

On other harnesses, proceed directly to code review.

3. Code Review (REQUIRED)

Every change gets reviewed before shipping. Default to Tier 1 and escalate to Tier 2 only when a concrete signal calls for it. Tier 2 is materially more expensive in time and tokens -- pay that cost when a signal justifies it, not as a default.

Tier 1 -- harness-native code review (default). Run your built-in code review command or skill (e.g., /review in Claude Code). Address blocking and suggested findings inline before Final Validation. Skip the Residual Work Gate. If the current harness has no built-in code review command or skill, escalate to Tier 2 -- Tier 1 cannot run, and "Every change gets reviewed" still applies.

Tier 2 -- `ce-code-review` (escalation). Invoke the ce-code-review skill with mode:autofix, passing plan:<path> when known. Then proceed to the Residual Work Gate.

Escalate to Tier 2 when any of the following is true:

• Sensitive surface touched. The diff modifies any of: authentication or authorization, payments or billing, data migrations or backfills, cryptography or secret handling, security-relevant configuration, public API or library contracts, or dependency manifests.
• Large and diffuse change. The diff exceeds >=400 changed lines and spans more than 3 directories or 2 distinct subsystems. Either alone is a soft signal; together they are an escalation trigger.
• Very large change. The diff exceeds >=1,000 changed lines regardless of diffusion.
• Plan or task explicitly requests it. The plan, the originating task, or another instruction in scope calls for a full / deep / thorough code review.

When the change is small, concentrated, and outside the sensitive surface list, Tier 1 is sufficient -- do not escalate "to be safe."

4. Residual Work Gate (REQUIRED when Tier 2 ran)

After Tier 2 code review completes, inspect the Residual Actionable Work summary it returned (or read the run artifact directly if the summary was not emitted). If one or more residual downstream-resolver findings remain, do not proceed to Final Validation until the user decides how to handle them.

Ask the user using the platform's blocking question tool (AskUserQuestion in Claude Code with ToolSearch select:AskUserQuestion pre-loaded if needed, request_user_input in Codex, ask_user in Gemini, ask_user in Pi (requires the pi-ask-user extension)). Fall back to numbered options in chat only when the harness genuinely lacks a blocking tool. Never silently skip the gate.

Stem: Code review found N residual finding(s) the skill did not auto-fix. How should the agent proceed?

Options (four or fewer, self-contained labels):

• Apply/fix now — loop back into review with focused fixes; the agent investigates each finding, applies changes where safe, and re-runs review.
• File tickets via project tracker — load references/tracker-defer.md in Interactive mode; the agent files tickets in the project's detected tracker (or gh fallback, or leaves them in the report if no sink exists) and proceeds to Final Validation.
• Accept and proceed — record the residual findings verbatim in a durable "Known Residuals" sink before shipping. If a PR will be created or updated in Phase 4, include them in the PR description's "Known Residuals" section (the agent owns this when calling ce-commit-push-pr). If the user later chooses the no-PR ce-commit path, create docs/residual-review-findings/<branch-or-head-sha>.md, include the accepted findings and source review-run context, stage it with the implementation commit, and mention the file path in the final summary. The user has acknowledged the risk, but the findings must not live only in the transient session.
• Stop — do not ship — abort the shipping workflow. The user will handle findings manually before re-invoking.

Skip this gate entirely when the review reported Residual actionable work: none. or when only Tier 1 was used. Do not proceed past this gate on an Accept and proceed decision until the agent has recorded whether the durable sink is PR Known Residuals or docs/residual-review-findings/<branch-or-head-sha>.md.

5. Final Validation

• All tasks marked completed
• Testing addressed -- tests pass and new/changed behavior has corresponding test coverage (or an explicit justification for why tests are not needed)
• Linting passes
• Code follows existing patterns
• Figma designs match (if applicable)
• No console errors or warnings
• If the plan has a Requirements section (or legacy Requirements Trace), verify each requirement is satisfied by the completed work
• If any Deferred to Implementation questions were noted, confirm they were resolved during execution

6. Prepare Operational Validation Plan (REQUIRED)

• Add a ## Post-Deploy Monitoring & Validation section to the PR description for every change.
• Include concrete:
• Log queries/search terms
• Metrics or dashboards to watch
• Expected healthy signals
• Failure signals and rollback/mitigation trigger
• Validation window and owner
• If there is truly no production/runtime impact, still include the section with: No additional operational monitoring required and a one-line reason.

Phase 4: Ship It

1. Prepare Evidence Context

Do not invoke ce-demo-reel directly in this step. Evidence capture belongs to the PR creation or PR description update flow, where the final PR diff and description context are available.

Note whether the completed work has observable behavior (UI rendering, CLI output, API/library behavior with a runnable example, generated artifacts, or workflow output). The ce-commit-push-pr skill will ask whether to capture evidence only when evidence is possible.

2. Update Plan Status

If the input document has YAML frontmatter with a status field, update it to completed:

   status: active  ->  status: completed

3. Commit and Create Pull Request

Load the ce-commit-push-pr skill to handle committing, pushing, and PR creation. The skill handles convention detection, branch safety, logical commit splitting, adaptive PR descriptions, and attribution badges.

When providing context for the PR description, include:

• The plan's summary and key decisions
• Testing notes (tests added/modified, manual testing performed)
• Evidence context from step 1, so ce-commit-push-pr can decide whether to ask about capturing evidence
• Figma design link (if applicable)
• The Post-Deploy Monitoring & Validation section (see Phase 3 Step 6)
• Any "Known Residuals" accepted in the Phase 3 Residual Work Gate, rendered as a dedicated section in the PR body with severity, file:line, and title per finding

If the user prefers to commit without creating a PR, load the ce-commit skill instead.

4. Notify User

• Summarize what was completed
• Link to PR (if one was created)
• Note any follow-up work needed
• Suggest next steps if applicable

Quality Checklist

Before creating PR, verify:

• [ ] All clarifying questions asked and answered
• [ ] All tasks marked completed
• [ ] Testing addressed -- tests pass AND new/changed behavior has corresponding test coverage (or an explicit justification for why tests are not needed)
• [ ] Linting passes (use linting-agent)
• [ ] Code follows existing patterns
• [ ] Figma designs match implementation (if applicable)
• [ ] Evidence decision handled by ce-commit-push-pr when the change has observable behavior
• [ ] Commit messages follow conventional format
• [ ] PR description includes Post-Deploy Monitoring & Validation section (or explicit no-impact rationale)
• [ ] Code review completed (Tier 1 harness-native or Tier 2 ce-code-review)
• [ ] PR description includes summary, testing notes, and evidence when captured
• [ ] PR description includes Compound Engineered badge with accurate model and harness

Code Review Tiers

Every change gets reviewed. Default to Tier 1; escalate to Tier 2 only on a concrete signal. Tier 2 is materially more expensive in time and tokens.

Tier 1 -- harness-native code review (default). Run your built-in code review command or skill (e.g., /review in Claude Code). Address blocking and suggested findings inline. If the current harness has no built-in code review command or skill, escalate to Tier 2 -- Tier 1 cannot run.

Tier 2 -- `ce-code-review` (escalation). Invoke ce-code-review mode:autofix with plan:<path> when available. Safe fixes are applied automatically; residual work routes through the Residual Work Gate.

Escalate to Tier 2 when any of these holds:

• Sensitive surface touched (auth/authz, payments/billing, data migrations or backfills, cryptography or secrets, security-relevant config, public API or library contracts, dependency manifests)
• Large and diffuse change (>=400 changed lines AND >3 directories or 2 subsystems)
• Very large change (>=1,000 changed lines)
• Plan or task explicitly requests a full / deep / thorough code review

Tracker Detection and Defer Execution

This reference covers how Defer actions file tickets in the project's tracker. It is loaded by SKILL.md when Interactive mode's routing question needs to decide whether to offer option C (File tickets), when the walk-through's Defer option executes, and when the bulk-preview of option C is shown. It is also loaded by autonomous callers (e.g., lfg) that need to file residual actionable findings without user prompts — see Execution Modes below.

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Execution Modes

Tracker-defer has two execution modes. The caller selects one; the detection, fallback chain, and ticket composition are shared.

Interactive mode (default)

Used by ce-code-review Interactive mode's routing question, walk-through Defer actions, and bulk-preview option C. All user-facing prompts fire:

• First Defer of the session with a generic (non-named) label confirms the effective tracker choice.
• Execution failures prompt with Retry / Fall back to next sink / Convert to Skip.
• Labels in the routing question reflect named_sink_available (name the tracker) vs fallback generics.

Non-interactive mode

Used by autonomous callers like lfg that must not prompt. All blocking questions are skipped; the fallback chain is executed silently in order. Behavior:

• No confirmation on the first generic-label Defer; proceed directly.
• On execution failure, automatically fall to the next tier without prompting. Record the failure.
• On total chain exhaustion (every tier failed or no sink available), return findings in the no_sink bucket so the caller can route them to another surface (e.g., inline them in a PR description).
• Return a structured result: { filed: [{ finding_id, tracker, url }], failed: [{ finding_id, tracker, reason }], no_sink: [{ finding_id, title, severity, file, line }] }.

The caller decides how to surface the result to the user. The non-interactive mode treats "no sink available" as a data-producing outcome, not a prompt trigger.

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Detection

The agent determines the project's tracker from whatever documentation is obvious. Primary sources: CLAUDE.md and AGENTS.md at the repo root and in relevant subdirectories. Supplementary signals (when primary documentation is ambiguous): CONTRIBUTING.md, README.md, PR templates under .github/, visible tracker URLs in the repo.

A tracker can be surfaced via MCP tool (e.g., a Linear MCP server), CLI (e.g., gh), or direct API. All are acceptable. The detection output is a tuple with two availability flags — one for the named tracker specifically (drives label confidence in Interactive mode) and one for the full fallback chain (drives whether Defer is offered at all):

{ tracker_name, confidence, named_sink_available, any_sink_available }

Where:

• tracker_name — human-readable name ("Linear", "GitHub Issues", "Jira"), or null when detection cannot identify a specific tracker
• confidence — high when the tracker is named explicitly in documentation (or via a linked URL to a specific project/workspace) and is unambiguously the project's canonical tracker; low when the signal is thin, conflicting, or implied only
• named_sink_available — true only when the agent can actually invoke the detected tracker (MCP tool is loaded, CLI is authenticated, or API credentials are in environment); false when the tracker is documented but no tool reaches it, or when no tracker is found at all. Drives label confidence: inline tracker naming requires this to be true.
• any_sink_available — true when any tier in the fallback chain (named tracker or GitHub Issues via gh) can be invoked this session. Drives whether Defer is offered in Interactive mode, and drives the no_sink bucket in Non-interactive mode.

Detection is reasoning-based. Do not maintain an enumerated checklist of files to read. Read the obvious sources and form a confident conclusion; when the obvious sources don't resolve, the label falls back to generic wording and the agent confirms with the user before executing (Interactive mode only).

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Probe timing and caching

Availability probes run at most once per session and only when Defer execution is imminent. Never speculatively at review start, never per-Defer, never per-walk-through-finding. The cached tuple is reused for every Defer action in the same run.

Typical probe sequence:

1. Read CLAUDE.md / AGENTS.md for tracker references. If nothing found, set tracker_name = null, confidence = low. 2. Probe the named tracker when one was found. For GitHub Issues, run gh auth status and gh repo view --json hasIssuesEnabled. For Linear or other MCP-backed trackers, verify the relevant MCP tool is loaded and responsive. For API-backed trackers, verify credentials in environment. Set named_sink_available from the probe result. 3. Probe the GitHub Issues fallback to compute `any_sink_available`. Even when the named tracker was found and probed, gh matters for the no_sink bucket decision so that a run with no documented tracker but working gh still offers Defer.

• If named_sink_available = true: any_sink_available = true (no further probes needed).
• Otherwise, probe GitHub Issues via gh auth status + gh repo view --json hasIssuesEnabled (skip if already probed in step 2). If it works, any_sink_available = true.
• Otherwise, any_sink_available = false.

When Interactive mode's routing question is skipped entirely (R2 zero-findings case), no probes run. When the cached tuple is reused across a session, any named_sink_available = true from the session's first probe stays cached — do not re-probe per Defer.

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Label logic (Interactive mode)

• When confidence = high AND named_sink_available = true: the routing question's option C and the walk-through's per-finding Defer option both include the tracker name verbatim. Example: File a Linear ticket per finding, Defer — file a Linear ticket.
• When any_sink_available = true but either confidence = low or named_sink_available = false (a fallback tier is working instead): the labels read generically — File an issue per finding, Defer — file a ticket. Before executing the first Defer of the session, the agent confirms the effective tracker choice with the user using the platform's blocking question tool.
• When any_sink_available = false: option C is omitted from the routing question, option B (Defer) is omitted from the walk-through per-finding options, and the agent tells the user why in the routing question's stem.

Non-interactive mode skips label decisions entirely — it acts silently on the detected sink.

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Fallback chain

When the named tracker is unavailable or no tracker is named, fall back in this order. Prefer the project's detected tracker; use gh only when no named tracker was found or the named one is unreachable.

1. Named tracker (MCP tool, CLI, or API the agent can invoke directly, identified via Detection above) 2. GitHub Issues via `gh` — when gh auth status succeeds and the current repo has issues enabled (gh repo view --json hasIssuesEnabled returns true) 3. No sink — findings remain in the review report's residual-work section (Interactive mode) or are returned in the no_sink bucket for the caller to route (Non-interactive mode). The agent does not re-display them through a transient surface.

Previously this chain included a third in-session fallback tier. That tier was removed because in-session tasks do not survive past the session and therefore do not meet the "durable filing" intent of a Defer action. When no durable tracker exists, the correct behavior is to leave findings in the report (Interactive) or return them to the caller (Non-interactive).

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Ticket composition

Every Defer action creates a ticket with the following content, adapted to the tracker's capabilities:

• Title: the merged finding's title (schema-capped at 10 words).
• Body:
• Plain-English problem statement — reads the persona-produced why_it_matters from the contributing reviewer's artifact file at /tmp/compound-engineering/ce-code-review/<run-id>/{reviewer}.json, using the same file + line_bucket(line, +/-3) + normalize(title) matching headless mode uses (see SKILL.md Stage 6 detail enrichment). Falls back to the merged finding's title, severity, file, and suggested_fix (when present) when no artifact match is available — these fields are guaranteed in the merge-tier compact return.
• Suggested fix (when present in the finding's suggested_fix).
• Evidence (direct quotes from the reviewer's artifact).
• Metadata block: Severity: <level>, Confidence: <score>, Reviewer(s): <list>, Finding ID: <fingerprint>.
• Labels (when the tracker supports labels): severity tag (P0, P1, P2, P3) and, when the tracker convention supports it, a category label sourced from the reviewer name.
• Length cap: when the composed body would exceed a tracker's body length limit, truncate with ... (continued in ce-code-review run artifact: /tmp/compound-engineering/ce-code-review/<run-id>/) and include the finding_id in both the truncated body and the metadata block so the artifact is discoverable.

The finding_id is a stable fingerprint composed as normalize(file) + line_bucket(line, +/-3) + normalize(title) — the same fingerprint used by the merge pipeline.

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Failure path

When ticket creation fails at execution (API error, auth expiry mid-session, rate limit, malformed body rejected, 4xx/5xx response):

Interactive mode: surface the failure inline and ask the user using the platform's blocking question tool.

Stem:

Defer failed: <tracker name> returned <error summary>. How should the agent handle this finding?

Options:

• Retry on <tracker> — re-attempt the same tracker once more (useful for transient errors)
• Fall back to next sink — move this finding's Defer to the next tier in the fallback chain (e.g., from Linear to GitHub Issues)
• Convert to Skip — record the failure — abandon this Defer, note the failure in the completion report's failure section, and continue the walk-through or bulk flow

Non-interactive mode: do not prompt. Automatically fall through to the next tier. If every tier fails, record the finding in the failed bucket of the structured return and continue. If the chain exhausts with no sink ever available, the finding ends up in the no_sink bucket.

When a high-confidence named tracker fails at execution, the cached named_sink_available is set to false for the rest of the session. Subsequent Defer actions fall straight through to the next tier without retrying a confirmed-broken sink. any_sink_available is only downgraded to false when every tier has been confirmed broken — a failed Linear call that succeeds via gh keeps any_sink_available = true.

Only when ToolSearch explicitly returns no match or the tool call errors — or on a platform with no blocking question tool — fall back to numbered options and waiting for the user's reply (Interactive mode only).

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Per-tracker behavior

Concrete behavior per tracker at execution time. The agent may invoke any of these through the appropriate interface (MCP, CLI, or API) — the choice depends on what is available in the current environment.

When uncertain, prefer "drop with explicit user-facing notice" over "pass through silently and hope." A Defer that produces no durable artifact and no user message is data loss.

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Cross-platform notes

The question-tool name varies by platform. In Interactive mode, use the platform's blocking question tool (AskUserQuestion in Claude Code, request_user_input in Codex, ask_user in Gemini, ask_user in Pi (requires the pi-ask-user extension)). In Claude Code the tool should already be loaded from the Interactive-mode pre-load step — if it isn't, call ToolSearch with query select:AskUserQuestion now. Fall back to numbered options in chat only when the harness genuinely lacks a blocking tool — ToolSearch returns no match, the tool call explicitly fails, or the runtime mode does not expose it (e.g., Codex edit modes without request_user_input). A pending schema load is not a fallback trigger. Never silently skip the question.

Non-interactive mode is platform-agnostic: it never prompts, so the platform's question tool is not relevant.