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.claude/skills/boshu2-converter/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 55% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 136% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 50% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 35% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 89% | 0% |
Parse AgentOps skills into a universal SkillBundle format, then convert to target agent platforms.
The intermediate SkillBundle is what keeps conversions honest: every target reads the same parsed contract, so a rendering bug is a target-adapter bug, never a silent reinterpretation of the source. If two targets disagree about a skill's content, the bundle — not either output — arbitrates.
This is not the owner of the shipped skills-codex/** projection: that path is generated and gated by scripts/codex-sync.sh via scripts/regen-all.sh. This converter is an ad-hoc, out-of-tree exporter (Codex, Cursor) that writes under .agents/projections/converter/; it never mutates skills-codex/**. When the shipped Codex twin and this exporter disagree, the shipped path wins.
Named failure mode — projection editing: fixing a rendering problem by hand-editing the converted output, which the next conversion clean-writes away.
Anti-pattern: merging new output into an existing target directory to preserve local tweaks. Corrective: fix the source skill or the adapter, then re-run the clean-write conversion.
The converter runs a three-stage pipeline:
parse --> convert --> writeRead the source skill directory and produce a SkillBundle:
--- markers)---)references/ and scripts/references/skill-bundle-schema.md)Transform the SkillBundle into the target platform's format:
| Target | Output Format | Status | |--------|---------------|--------| | codex | Codex SKILL.md + prompt.md | Implemented | | cursor | Cursor .mdc rule + optional mcp.json | Implemented |
The Codex adapter produces a SKILL.md with YAML frontmatter (name, description) plus rewritten body content and a prompt.md. 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 normalizes foreign-runtime invocation syntax and paths, rewrites unsupported primitive labels to runtime-neutral wording, and preserves current flat ao CLI commands. It also deduplicates repeated runtime headings while preserving section content. Non-generated resource files and directories are copied with parity checks. Descriptions are truncated to 1024 characters 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.
Write the converted output to disk.
.agents/projections/converter/<target>/<skill-name>/bash# 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]
| Argument | Required | Description | |----------|----------|-------------| | skill-dir | Yes (or --all) | Path to skill directory (e.g. skills/council) | | target | Yes | Target platform: codex, cursor, or test | | output-dir | No | Override output location. Default: .agents/projections/converter/<target>/<skill-name>/ | | --all | No | Convert all skills in skills/ directory | | --codex-layout | No | Codex-only layout mode: modular (default) or inline (legacy inlined refs/scripts) |
SKILL.md + prompt.md) with runtime-neutral rewrites and flat ao CLI preservation. Default is modular output with copied resources and a local-resource index; pass --codex-layout inline for legacy inlined refs/scripts. Missing copied resources fail fast..mdc rule file + optional mcp.json). Output: <dir>/<name>.mdc and optionally <dir>/mcp.json.To add a new target platform:
scripts/convert.sh (pattern: convert_<target>)references/ if the target format needs documentationCaller asks: Convert skills/council to Codex format.
What happens:
skills/council/SKILL.md frontmatter, markdown body, and any references/ and scripts/ files into a SkillBundle.SKILL.md (body + inlined references + scripts as code blocks) and a prompt.md (Codex prompt referencing the skill)..agents/projections/converter/codex/council/.Result: A Codex-compatible skill package ready to use with OpenAI Codex CLI.
Caller asks: Convert all canonical skills to Cursor format.
What happens:
skills/ and parses each into a SkillBundle..mdc rule file with YAML frontmatter and body content, budget-fitted to 100KB max. Skills referencing MCP servers also get a mcp.json stub..agents/projections/converter/cursor/<skill-name>/.Result: All skills are available as Cursor rules, ready to drop into a .cursor/rules/ directory.
| Problem | Cause | Solution | |---------|-------|----------| | parse error: no frontmatter found | SKILL.md is missing the --- delimited YAML frontmatter block | Add frontmatter with at least name: and description: fields, or run Heal Skill on the source package first | | Cursor .mdc output is missing references | Total bundle size exceeded the 100KB budget limit | The 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 files | Previous conversion artifacts remain | This is expected -- the converter clean-writes by deleting the target directory before writing. If old files persist, manually delete .agents/projections/converter/<target>/<skill>/ | | --all skips a skill directory | The directory has no SKILL.md file | Ensure each skill directory contains a valid SKILL.md. Run Heal Skill to detect empty directories | | Codex prompt.md description is truncated | The skill description exceeds 1024 characters | This 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 check | A resource entry from source skill wasn't copied to output | Ensure source entries are readable and copyable (including nested files). Re-run conversion; failure is intentional to prevent drift between skills/ and converted output |
.agents/projections/converter/<target>/<skill-name>/ by default, or the exact caller-supplied output directory.SKILL.md, prompt.md, and copied resources; Cursor emits <skill-name>.mdc and optional mcp.json; test emits the raw bundle representation.bash skills/converter/scripts/convert.sh <skill-dir> <target> <output-dir> and require zero; treat parse, budget, write, or passthrough-parity failure as nonzero and incomplete.references/skill-bundle-schema.md -- SkillBundle interchange format specification| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 5,004 | 10,136 | +103% | 1 | 1 | 0% | 249 | 2,655 | +966% | 0 | 0 | — |
case-02 | fail→fail | 2,349 | 6,176 | +163% | 1 | 1 | 0% | 296 | 2,596 | +777% | 0 | 0 | — |
case-03 | fail→pass | 10,615 | 4,795 | -55% | 1 | 1 | 0% | 1,945 | 3,020 | +55% | 0 | 0 | — |
case-04 | fail→pass | 7,316 | 2,771 | -62% | 1 | 1 | 0% | 1,168 | 2,760 | +136% | 0 | 0 | — |
case-05 | fail→pass | 12,112 | 3,308 | -73% | 1 | 1 | 0% | 1,880 | 2,819 | +50% | 0 | 0 | — |
case-06 | fail→pass | 12,669 | 2,157 | -83% | 1 | 1 | 0% | 1,928 | 2,606 | +35% | 0 | 0 | — |
case-07 | pass→pass | 15,723 | 2,856 | -82% | 1 | 1 | 0% | 2,457 | 2,739 | +11% | 0 | 0 | — |
case-08 | fail→pass | 9,999 | 2,148 | -79% | 1 | 1 | 0% | 1,393 | 2,635 | +89% | 0 | 0 | — |
case-09 | fail→pass | 20,065 | 2,051 | -90% | 1 | 1 | 0% | 1,521 | 2,670 | +76% | 0 | 0 | — |
case-10 | pass→pass | 10,066 | 4,490 | -55% | 1 | 1 | 0% | 1,480 | 2,880 | +95% | 0 | 0 | — |
case-11 | fail→pass | 10,382 | 4,683 | -55% | 1 | 1 | 0% | 1,614 | 2,955 | +83% | 0 | 0 | — |
case-12 | pass→pass | 11,006 | 4,411 | -60% | 1 | 1 | 0% | 1,623 | 2,948 | +82% | 0 | 0 | — |
case-13 | fail→fail | 5,675 | 2,270 | -60% | 1 | 1 | 0% | 807 | 2,742 | +240% | 0 | 0 | — |
case-14 | pass→pass | 3,973 | 1,963 | -51% | 1 | 1 | 0% | 594 | 2,568 | +332% | 0 | 0 | — |
case-15 | fail→pass | 10,535 | 5,116 | -51% | 1 | 1 | 0% | 1,592 | 3,131 | +97% | 0 | 0 | — |
case-16 | pass→pass | 5,936 | 2,582 | -57% | 1 | 1 | 0% | 900 | 2,701 | +200% | 0 | 0 | — |
case-17 | pass→pass | 21,586 | 3,079 | -86% | 1 | 1 | 0% | 1,850 | 2,824 | +53% | 0 | 0 | — |
case-18 | fail→fail | 7,888 | 1,817 | -77% | 1 | 1 | 0% | 1,378 | 2,564 | +86% | 0 | 0 | — |
case-19 | pass→pass | 8,074 | 3,309 | -59% | 1 | 1 | 0% | 1,210 | 2,861 | +136% | 0 | 0 | — |
case-20 | fail→pass | 8,285 | 4,979 | -40% | 1 | 1 | 0% | 1,588 | 3,322 | +109% | 0 | 0 | — |
case-21 | pass→pass | 7,089 | 4,063 | -43% | 1 | 1 | 0% | 1,131 | 3,025 | +167% | 0 | 0 | — |
case-22 | fail→pass | 16,594 | 4,535 | -73% | 1 | 1 | 0% | 1,910 | 3,064 | +60% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 20 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +45 percentage points is the difference between those two pass rates over the 20 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.