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Defame1297 4a5c3c0cff feat(kyberforge): enforce the ADR-0020 context contract for skills and agents

Skill name+description pairs are preloaded into every session, costing
~6,200 tokens across 39 skills before any skill is invoked. The authoring
rules mandated that growth: skill-author:104 and description-quality.md:21
both required padding, while skill-author:102 (the deflating rule) had no
FAIL condition behind it.

Gates (blocking, no baseline file):
- description 250 chars SUGGESTION / 400 FAIL, measured on the folded
  YAML value
- body-only 600 words SUGGESTION / 900 FAIL, independent of the unchanged
  whole-file 2770-word / 500-line spec backstop
- every boundary-clause routing target must resolve to a real skill or
  agent; catches skill-improve, neuledge-context and gitea-labels
- agents take the description gates but deliberately no body gate; a test
  pins that absence

Vale: DescriptionOpener widened to ^This\b, new CompositionNote rule
banning architecture notes from descriptions. 10 hits, 0 false positives.

Kyberforge's own four skills retrofitted: descriptions 3,364 -> 938 chars
(-72%), bodies 8,306 -> 2,487 words (-70%), all via the apm-workflow
dispatch pattern. Fixes the skill-improve dangling route and the
agent-author misroute to manual review.

Also fixes a pre-existing false positive where any line-initial 'read '
was flagged as interactive input, which had already caused two scripts to
be rewritten around it.

Refs: ADR-0020

2026-08-14 21:13:13 +00:00

3.4 KiB

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source_keys

agentskills-best-practices

agentskills-evaluating-skills

agentskills-optimizing-descriptions

Improving an existing skill

Return to SKILL.md Step 4 once Step 4 below is done — validation, versioning and commit verification are shared with the create flow and are not repeated here.

Step 1 — Verify inputs

Confirm the skill directory path exists and that at least one improvement signal is present in the conversation or a referenced file.

If the skill directory is missing, ask for it. If no signals are present, stop: "This skill applies existing signals to a skill. For a blind review without signals, use /skill-audit instead."

Signals can come from anywhere in the conversation or referenced files:

Grill session output (most common predecessor in the factory sequence)
/skill-audit findings (PASS/FAIL/SUGGESTION punch list)
Human feedback (feedback.json, inline in conversation, PR or issue comments)
Session context describing what went wrong

Also verify the name field in frontmatter matches the skill's directory name exactly.

Step 2 — Gather and group signals

Read the current skill files (SKILL.md and any files in scripts/, references/, assets/, tests/). Then collect all signals from the conversation and any file paths the user has referenced.

Group signals by root cause, not symptom. Patching per symptom is the default failure mode: three eval failures may all trace to one missing instruction. Ask: "What single gap in the skill causes this cluster of failures?" One root cause → one fix. Do not make a separate edit for each symptom.

Example:
- Session context: output format is wrong on every run
- Audit finding: no output template defined
- User feedback: "I always have to ask it to format the output"
→ Root cause: SKILL.md has no output format specification → one fix: add an output template

Step 3 — Announce planned changes

Before editing, state:

Which root causes were identified and what evidence supports each
Which files will be changed and what will change in each

Then proceed — edits are reversible via git, no approval checkpoint needed.

Step 4 — Apply changes

Edit any file in the skill directory that the signals point to: SKILL.md, scripts/, references/, assets/, tests/, README.md.

Generalize, do not patch. Find the underlying gap, not the specific example that failed. A fix scoped only to the test cases you have seen will overfit and perform worse on new inputs.

Keep it lean. Remove instructions that are not pulling their weight. For every sentence you add, ask: "Would the agent get this wrong without it?" A shorter, focused skill consistently outperforms an exhaustive one.

Explain the why. Reasoning-based instructions outperform rigid directives. If you find yourself writing a rule in all caps (ALWAYS/NEVER), reframe it: explain why the behavior matters so the agent can apply judgment in edge cases.

Retrofit before extending. Any edit to a skill that predates ADR-0020 has to bring it into the contract first — the gates are hot and carry no baseline file, so a one-line fix to a non-compliant skill cannot be committed until the description and body meet references/contract.md. Treat that retrofit as part of the same change, not a follow-up.

If a signal points to a script or reference file, edit that file directly rather than adding a workaround in SKILL.md.

Then return to SKILL.md Step 4.

3.4 KiB Raw Blame History