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harness-research

Research one agent harness's release (docs, source, runtime) and fill its capability cells in scripts/harness_capabilities.py with cited evidence. Use after a harness version bump, when just harness-probe reports re-research, or when capability cells read unknown.

Quality

81%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

68%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a maximally lean delegation stub that is token-efficient and cleanly points one level deep to the shared skill, but it delegates everything: no task steps, no validation checkpoints for the batch cell-filling work, and no overview of what the shared skill contains. It works only insofar as the external shared skill is guaranteed to be present and loadable.

Suggestions

Add a 3-5 line overview of the shared skill's workflow (research steps, cell-filling conventions, citation format) so the stub orients the reader before delegation.

Mention where validation lives (e.g., verify cited evidence and re-run harness-probe checks after filling cells) so the batch editing work has a checkpoint even at the stub level.

Reference the shared skill via a path that is stable across environments (or bundle a copy/symlink under the skill directory), since `~/.agents/skills/...` is machine-specific and unverifiable from the bundle.

DimensionReasoningScore

Conciseness

The body is two lines: a generated-file marker ("Generated by scripts/agent-harnesses.py; do not edit directly.") and a single delegation instruction. There is no padding and no explanation of concepts Claude already knows; every token is operational. This matches the lean-and-efficient anchor exactly.

5 / 5

Actionability

"Load and follow the shared skill at `~/.agents/skills/harness-research/SKILL.md`" is a concrete, executable directive with an exact path, but it is the only guidance present — how to research the release, fill cells, or format citations is entirely absent from the body. Not 4 because the gap is the whole task detail, not a minor one; not 2 because the written instruction is a precise, executable step rather than a high-level hint.

3 / 5

Workflow Clarity

The single delegation step is unambiguous, but the multi-step research-and-edit workflow promised by the description has no sequence or checkpoints in the body, and the batch operation of filling capability cells has no validation guidance, which caps this at 3. Not 2 because the one step that is written is coherent and precise.

3 / 5

Progressive Disclosure

The body is a single, clearly signaled, one-level-deep pointer with trivial navigation and no nested references; no bundle directories (references/, scripts/, assets/) exist, and the pointer targets an absolute home-directory path outside the skill bundle. Not 5 because the body provides no overview or orientation — the reader learns nothing about the skill's scope before following the link.

4 / 5

Total

15

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it clearly and explicitly states both what the skill does and when to use it, with concrete actions, a specific output artifact, and highly distinctive project-scoped triggers. The only minor gap is the absence of synonym variations for the trigger terms.

DimensionReasoningScore

Specificity

"Research one agent harness's release (docs, source, runtime)" and "fill its capability cells in scripts/harness_capabilities.py with cited evidence" name several concrete actions with specific sources and a named target file. Not 5 because it does not itemize which capabilities are covered or how the research is performed; not 3 because it goes beyond 1-2 generic actions by naming the output artifact and evidence requirement.

4 / 5

Completeness

Explicitly answers both: what ("Research one agent harness's release (docs, source, runtime) and fill its capability cells in scripts/harness_capabilities.py with cited evidence") and when ("Use after a harness version bump, when just harness-probe reports re-research, or when capability cells read unknown") with concrete trigger phrases — a direct match to the anchor-5 example pattern.

5 / 5

Trigger Term Quality

Trigger phrases "harness version bump", "harness-probe reports re-research", and "capability cells read unknown" are natural phrases for this project's workflow and cover the main trigger scenarios. Not 5 because no synonyms or variations are included (e.g., upgrade, new release, release notes); not 3 because the coverage of actual trigger cases is specific and good rather than sparse.

4 / 5

Distinctiveness Conflict Risk

The niche is highly specific: a named target file (scripts/harness_capabilities.py) and project-specific triggers (harness-probe reports, capability cells reading unknown) make conflict with other skills minimal. Not 4 because no plausible overlap risk exists — the triggers could not naturally invoke a different skill.

5 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

15

/

16

Passed

Repository

phatblat/dotfiles

Path

.claude/skills/harness-research/SKILL.md

Reviewed

Table of Contents

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