Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
aws-samples avatar

Sdlc Agents Select

  • 1 installs
  • 6 repo stars
  • Updated July 23, 2026
  • aws-samples/sample-agents-for-product-teams

sdlc-agents-select is a skill that filters the SDLC agent roster against a team's existing tools and records the chosen agents to a selection.yaml file.

About

This skill helps choose which SDLC agents to install based on the tools a team already uses. It filters the fleet roster against the user's PM tool, source control, and chat platform, hides agents whose requirements are not met, and presents an opinionated Recommended and Optional grouping. A developer uses it after tool discovery to record an agent selection. It writes the chosen agents and toolchain to .sdlc-agents/selection.yaml.

  • Picks which SDLC agents to install by matching the user's existing tools
  • Filters the fleet roster to shipping agents whose hard requirements are met
  • Records the selection to .sdlc-agents/selection.yaml at the target project root

Sdlc Agents Select by the numbers

  • 1 all-time installs (skills.sh)
  • Ranked #14,102 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Jul 27, 2026 (Skillselion catalog sync)
At a glance

sdlc-agents-select capabilities & compatibility

Capabilities
agent selection · tool discovery · fleet configuration
Works with
github · jira · slack · salesforce
Use cases
planning · project management · orchestration
From the docs

What sdlc-agents-select says it does

Only agents with `Status: shipping` have working code and can be installed today.
SKILL.md
Write `.sdlc-agents/selection.yaml` at the **target project root**
SKILL.md
npx skills add https://github.com/aws-samples/sample-agents-for-product-teams --skill sdlc-agents-select

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs1
repo stars6
Last updatedJuly 23, 2026
Repositoryaws-samples/sample-agents-for-product-teams

What it does

Select which SDLC agents to install by matching the fleet roster against the team's existing tools.

Who is it for?

Choosing which shipping SDLC agents fit a team's PM, source control, and chat stack, then recording the selection.

Skip if: Presenting non-shipping or design-only agents, which the skill explicitly excludes.

When should I use this skill?

When the user needs to pick which SDLC agents to install based on the tools they already use.

What you get

  • .sdlc-agents/selection.yaml with selected agents and toolchain

By the numbers

  • Roster lists four shipping agents: workitems, researcher, docwriter, adr

Files

SKILL.mdMarkdownGitHub ↗

Select the right agents for this customer

Prerequisites

You should already know (from earlier conversation):

  • PM tool in use (Asana / Jira / Linear / etc. / none)
  • Source control (GitHub / GitLab / Bitbucket / etc.)
  • Chat platform (Slack / Teams / etc. / none)
  • Optional signals: Salesforce, Datadog/observability, Figma

If you don't know these, stop and ask the user. Do not guess.

The roster

Match this table against what the user has. Hide rows that require a tool the user doesn't use. Don't present unreachable agents; it's noise.

Only agents with Status: shipping have working code and can be installed today. The others have design docs under docs/agents/<name>.md but no runtime — don't present them to the user even if their tool requirements match. If the user explicitly asks about one, tell them it's planned and point them at docs/agents/<name>.md.

AgentStatusWhat it doesHard requirementsNice-to-have
workitemsshippingPO/PM. Decomposes feature asks into tracker issues; status reports; risk detection.PM tool and source controlSlack for weekly status
researchershippingBusiness analyst. Research synthesis, competitive intel, backlog analysis.PM toolWeb search (Tavily, SerpAPI, Perplexity)
docwritershippingTechnical writer. API docs, release notes, doc PRs.Source controlPM tool for feature context
adrshippingTags issues + reviews PRs against the ADRs that govern the work.Source control and an ADR directory that already exists-

ADR agent has a repo-specific check

The adr agent is useful only when the target repo already has an ADR library — it can't tag work against decisions that don't exist. Before including adr in any recommendation, confirm the target repo actually has ADRs.

Check the target repo, not the installer cwd. The top-level flow resolves TARGET_REPO as an absolute path before invoking this skill; all filesystem checks here run against that path. If TARGET_REPO isn't set, stop and ask the top-level flow to resolve it — don't fall back to ls in the current directory, since that will misdetect when the installer and target are different repos.

Check the common ADR locations under TARGET_REPO (for example "$TARGET_REPO/adrs", "$TARGET_REPO/ADRs", "$TARGET_REPO/docs/adrs", "$TARGET_REPO/docs/decisions", "$TARGET_REPO/architecture/decisions"). If one is present and non-empty, report which path you found and ask the user to confirm it's the right one. If none are present, ask the user whether they keep ADRs at a non-standard path before concluding there are none.

  • Yes, at one of those paths: include adr in Optional. Record the path in selection.yaml under adr.dir (relative to the target repo root).
  • Yes, at a non-standard path (e.g. architecture/decisions/, docs/decisions/): include adr in Optional; record the custom path.
  • No ADRs yet: omit adr from the presentation entirely. Don't recommend it, don't list it as skipped — the user doesn't need to see it as an option. If they explicitly ask about it, tell them: "The `adr` agent needs an ADR library in the target repo to link against. Start writing ADRs in `docs/adrs/` there first, then re-run selection."

The agent has no fallback behavior for "no ADRs" — it's not useful without them, so don't ship it half-configured.

Present to the user

1. Filter the table to agents that are shipping and whose hard requirements are met. (For adr, this includes the ADR-directory check above — don't show it if the repo doesn't have ADRs.) 2. Group into two categories — Recommended and Optional — and print each with a one-line purpose. The Recommended bucket should be anchored to what tools the user has, e.g.:

Based on your setup (Asana + GitHub + Slack), I recommend starting with:
- workitems — drives Asana ↔ GitHub decomposition and weekly status to Slack
- docwriter — opens GitHub doc PRs on merged code PRs
- researcher — synthesizes customer research into Asana stories

>

Optional add-ons that fit your stack: adr (if you have an ADR library).

3. Ask the user which to install. Accept three answers:

  • "just the recommended" → select the Recommended list
  • an explicit list (space- or comma-separated agent names)
  • "all" → select Recommended + Optional

4. Before recording, warn on redundant combinations:

  • adr without an ADR directory → won't find anything to link against (the ADR-directory check above should already have removed it)

Record the selection

Write .sdlc-agents/selection.yaml at the target project root ($TARGET_REPO/.sdlc-agents/selection.yaml), not in the installer repo:

# Generated by sdlc-agents-select. Edit by re-running the skill.
selected_at: 2026-04-29T00:00:00Z
toolchain:
  pm: asana         # or: jira, linear, trello, aha, none
  scm: github       # or: gitlab, bitbucket
  chat: slack       # or: teams, none
  support: null     # or: salesforce
  observability: null  # or: datadog, cloudwatch, grafana
agents:
  - workitems
  - docwriter
  - researcher
adr:                # only present if `adr` was selected
  dir: docs/adrs    # where the repo's ADRs live
aws:
  account_id: "123456789012"     # replace with the target AWS account
  region: <REGION>               # replace with the target region, e.g. us-west-2
  stage: dev

If the file exists, read it first, merge, and ask before overwriting any existing keys the user didn't re-confirm.

What not to do

  • Don't try to make every customer install the whole fleet. The interesting demo is a focused one.
  • Don't reorder the Recommended list arbitrarily — keep the ordering by "dependency": workitems first (the orchestrator), then researcher (feeds workitems), then docwriter (fed by workitems). Dependent agents after their producers.
  • Don't invent agents that aren't in the roster above. If a customer asks for an agent name we don't have (common: "@reviewer", "@qa"), tell them the closest match or flag it as a gap.

Related skills

AI & Agent Buildingagentsautomation

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.