Content
77%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
An exceptionally actionable, well-sequenced operational skill — every phase has executable commands, explicit checkpoints, and failure handling. Its weaknesses are a monolithic single-file structure with no bundled reference files (despite referencing an unbundled calibration script) and rationale/backstory sections that inflate token cost without aiding execution.
Suggestions
Move the prompt-injection, secrets, and PII regex pattern libraries (~50 lines) into references/security-patterns.md and read them only during Phase 2, keeping SKILL.md as a lean phase-by-phase overview.
Trim the 'What this skill is for' backstory and Phase 0.5's academic-citation framing to one or two sentences each — the model needs the calibration mechanics, not the pattern's provenance.
Bundle generate-calibration.py (and a generated calibration.md sample) in scripts/ alongside SKILL.md so the referenced files actually resolve within the skill distribution.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The bulk is dense operational payload (commands, regexes, templates), but it includes unnecessary explanation and rationale that could be trimmed: the "What this skill is for" backstory ("You've run it 5+ times manually — same shape every time"), the threat-model explainer ("the source is untrusted text being read by an LLM that has filesystem and shell access"), and Phase 0.5's academic citations ([[Filesystem-as-Feedback for Coding Agents]], [[Meta-Harness Paper (Lee et al, 2026)]]) which explain concepts the model already grasps. This is more than the 'minor instances' of the anchor-4 example but far from the padding of anchor 2. | 3 / 5 |
Actionability | Fully executable throughout: copy-paste-ready defuddle/unzip/git command blocks, complete prompt-injection and secrets regex libraries (e.g. "AKIA[0-9A-Z]{16}", "ghp_[A-Za-z0-9]{36}"), a gitleaks fallback, and exact fill-in templates for the Phase 4 write plan, security summary, and Phase 6 report. Specific commands cover the common source types (URL, PDF, local file, directory, zip). | 5 / 5 |
Workflow Clarity | Six phases are explicitly ordered ("Follow these phases in order. Do not skip phases") with validation checkpoints at every risky stage: mandatory security stop-and-wait ("If any HIGH-severity finding exists, stop and wait"), the Phase 4 checkpoint ("**Wait for the user.** Do not write anything until they say go"), a pre-write concurrent-write check (git fetch/status with behind/diverged handling), and failure handling ("If any step fails: **stop and report.** Do not partial-recover"). Feedback loops are explicit ("If they say 'edit plan', revise and re-show") and the Honesty rules act as a final checklist — a textbook anchor-5 workflow. | 5 / 5 |
Progressive Disclosure | The body is a monolithic ~360-line SKILL.md with no bundle files at all — no references/, scripts/, or assets/ — yet it references "~/.claude/skills/vault-ingest/generate-calibration.py" and "calibration.md" which are not part of the bundle. Content that clearly belongs in separate files is inlined (~50 lines of injection/secrets/PII regex libraries, full write-plan templates). Mitigating factors keep it at 3 rather than 2: sections are well-organized with clear headers, and references to the vault's own docs (Phase 0's CLAUDE.md / Vault Ingestion Contract / jobs files) are clearly signaled and one level deep. | 3 / 5 |
Total | 16 / 20 Passed |