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Converter

  • 1.2k installs
  • 416 repo stars
  • Updated August 5, 2026
  • boshu2/agentops

converter is an agentops skill that converts workflow artifacts between supported formats for standardized automation pipelines.

About

The converter skill in the boshu2 agentops collection transforms workflow artifacts between supported formats so downstream agentops steps receive normalized inputs. It fits pipelines where logs, manifests, task specs, or exported agent outputs must be converted before validation, reporting, or deployment stages. Agents invoke it when standardizing file formats, normalizing field names, or preparing converter outputs compatible with other agentops skills such as standards or deployment helpers. The skill expects explicit source and target format instructions and preserves traceability by noting conversion assumptions. Use inside broader agentops automation chains rather than as a standalone end-user utility.

  • Converts agentops workflow artifacts between supported formats.
  • Normalizes inputs for downstream validation or reporting steps.
  • Preserves conversion assumptions and traceability notes.
  • Integrates with other agentops skills in automation chains.
  • Requires explicit source and target format instructions.

Converter by the numbers

  • 1,245 all-time installs (skills.sh)
  • +26 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #246 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

converter capabilities & compatibility

Capabilities
artifact format conversion · field normalization for pipelines · traceability notes on assumptions · agentops chain integration · explicit source target mapping
Use cases
orchestration
From the docs

What converter says it does

converter
SKILL.md
npx skills add https://github.com/boshu2/agentops --skill converter

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Listed on Skillselion
Installs1.2k
repo stars416
Security audit3 / 3 scanners passed
Last updatedAugust 5, 2026
Repositoryboshu2/agentops

How do I normalize this agent workflow artifact into the format the next agentops step expects?

Convert agent workflow artifacts and formats within the agentops toolkit for standardized automation pipelines.

Who is it for?

Agents running boshu2 agentops pipelines that need format normalization between stages.

Skip if: Skip for arbitrary binary file conversion outside agentops workflow artifacts.

When should I use this skill?

User converts agentops workflow outputs or prepares standardized inputs for later pipeline steps.

What you get

Converted artifact in the target format with documented assumptions for downstream steps.

  • Converted skill files for target agent platform
  • SkillBundle intermediate representation

By the numbers

  • Uses skill_api_version 1 in the AgentOps skill manifest
  • Documents example conversion command /converter skills/council codex

Files

SKILL.mdMarkdownGitHub ↗

/converter -- Cross-Platform Skill Converter

Parse AgentOps skills into a universal SkillBundle format, then convert to target agent platforms.

Quick Start

/converter skills/council codex     # Convert council skill to Codex format
/converter skills/validate cursor       # Convert vibe skill to Cursor format
/converter --all codex              # Convert all skills to Codex

Pipeline

The converter runs a three-stage pipeline:

parse --> convert --> write

Stage 1: Parse

Read the source skill directory and produce a SkillBundle:

  • Extract YAML frontmatter from SKILL.md (between --- markers)
  • Collect the markdown body (everything after the closing ---)
  • Enumerate all files in references/ and scripts/
  • Assemble into a SkillBundle (see references/skill-bundle-schema.md)

Stage 2: Convert

Transform the SkillBundle into the target platform's format:

TargetOutput FormatStatus
codexCodex SKILL.md + prompt.mdImplemented
cursorCursor .mdc rule + optional mcp.jsonImplemented

The Codex adapter produces a SKILL.md with YAML frontmatter (name, description) plus rewritten body content and a prompt.md (Codex prompt referencing the skill). Default mode is modular: reference docs, scripts, and resources are copied as files and SKILL.md includes a local resource index instead of inlining everything. Optional inline mode preserves the older behavior by appending inlined references and script code blocks. Codex output rewrites known slash-skill references (for example /plan) to dollar-skill syntax ($plan), replaces Claude-specific paths/labels (including ~/.claude/, $HOME/.claude/, and /.claude/ path variants), normalizes common mixed-runtime terms (for example Claude Native Teams, claude-native-teams, and Claude session/runtime) to Codex-native phrasing, and rewrites Claude-only primitive labels to runtime-neutral wording. It preserves current flat ao CLI commands from the source skill rather than reintroducing deprecated namespace forms. It also deduplicates repeated "In Codex" runtime headings after rewrite while preserving section content. It preserves non-generated resource files/directories from the source skill (for example templates/, assets/, schemas/, examples/, agents/) and enforces passthrough parity (missing copied resources fail conversion). Descriptions are truncated to 1024 chars at a word boundary if needed.

The Cursor adapter produces a <name>.mdc rule file with YAML frontmatter (description, globs, alwaysApply: false) and body content. References are inlined into the body, scripts are included as code blocks. Output is budget-fitted to 100KB max -- references are omitted largest-first if the total exceeds the limit. If the skill references MCP servers, a mcp.json stub is also generated.

Stage 3: Write

Write the converted output to disk.

  • Default output directory: .agents/converter/<target>/<skill-name>/
  • Write semantics: Clean-write. The target directory is deleted before writing. No merge with existing content.

CLI Usage

# Convert a single skill
bash skills/converter/scripts/convert.sh <skill-dir> <target> [output-dir]
bash skills/converter/scripts/convert.sh --codex-layout inline <skill-dir> codex [output-dir]

# Convert all skills
bash skills/converter/scripts/convert.sh --all <target> [output-dir]

Arguments

ArgumentRequiredDescription
skill-dirYes (or --all)Path to skill directory (e.g. skills/council)
targetYesTarget platform: codex, cursor, or test
output-dirNoOverride output location. Default: .agents/converter/<target>/<skill-name>/
--allNoConvert all skills in skills/ directory
--codex-layoutNoCodex-only layout mode: modular (default) or inline (legacy inlined refs/scripts)

Supported Targets

  • codex -- Convert to OpenAI Codex format (SKILL.md + prompt.md) with codex-native rewrites (slash-to-dollar skills, .claude path variants to .codex, mixed-runtime term normalization to Codex phrasing, Claude primitive label neutralization, duplicate runtime-heading cleanup, and flat ao CLI preservation). Default is modular output with copied resources and a SKILL.md local-resource index; pass --codex-layout inline for legacy inlined refs/scripts. Converter enforces passthrough parity so missing copied resources fail fast. Output: <dir>/SKILL.md, <dir>/prompt.md, and copied resources.
  • cursor -- Convert to Cursor rules format (.mdc rule file + optional mcp.json). Output: <dir>/<name>.mdc and optionally <dir>/mcp.json.
  • test -- Emit the raw SkillBundle as structured markdown. Useful for debugging the parse stage.

Extending

To add a new target platform:

1. Add a conversion function to scripts/convert.sh (pattern: convert_<target>) 2. Update the target table above 3. Add reference docs to references/ if the target format needs documentation

Examples

Converting a single skill to Codex format

User says: /converter skills/council codex

What happens: 1. The converter parses skills/council/SKILL.md frontmatter, markdown body, and any references/ and scripts/ files into a SkillBundle. 2. The Codex adapter transforms the bundle into a SKILL.md (body + inlined references + scripts as code blocks) and a prompt.md (Codex prompt referencing the skill). 3. Output is written to .agents/converter/codex/council/.

Result: A Codex-compatible skill package ready to use with OpenAI Codex CLI.

Batch-converting all skills to Cursor rules

User says: /converter --all cursor

What happens: 1. The converter scans every directory under skills/ and parses each into a SkillBundle. 2. The Cursor adapter transforms each bundle into a .mdc rule file with YAML frontmatter and body content, budget-fitted to 100KB max. Skills referencing MCP servers also get a mcp.json stub. 3. Each skill's output is written to .agents/converter/cursor/<skill-name>/.

Result: All skills are available as Cursor rules, ready to drop into a .cursor/rules/ directory.

Troubleshooting

ProblemCauseSolution
parse error: no frontmatter foundSKILL.md is missing the --- delimited YAML frontmatter blockAdd frontmatter with at least name: and description: fields, or run /heal-skill --fix on the skill first
Cursor .mdc output is missing referencesTotal bundle size exceeded the 100KB budget limitThe converter omits references largest-first to fit the budget. Split large reference files or move non-essential content to external docs
Output directory already has old filesPrevious conversion artifacts remainThis is expected -- the converter clean-writes by deleting the target directory before writing. If old files persist, manually delete .agents/converter/<target>/<skill>/
--all skips a skill directoryThe directory has no SKILL.md fileEnsure each skill directory contains a valid SKILL.md. Run /heal-skill to detect empty directories
Codex prompt.md description is truncatedThe skill description exceeds 1024 charactersThis is by design. The converter truncates at a word boundary to fit Codex limits. Shorten the description in SKILL.md frontmatter if the truncation point is awkward
Conversion fails with passthrough parity checkA resource entry from source skill wasn't copied to outputEnsure source entries are readable and copyable (including nested files). Re-run conversion; failure is intentional to prevent drift between skills/ and converted output

References

  • references/skill-bundle-schema.md -- SkillBundle interchange format specification

Reference Documents

  • references/skill-bundle-schema.md

Related skills

How it compares

Pick Converter when source skills live in AgentOps format and must ship to multiple agent IDEs from one pipeline.

FAQ

What does the agentops converter skill do?

It transforms workflow artifacts between supported formats for downstream agentops steps.

Does it run standalone?

It is intended inside agentops automation chains with explicit source and target formats.

What must agents specify?

Source format, target format, and any field mapping or assumptions for traceability.

Is Converter safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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