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result-to-claim

Use when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. A secondary Codex agent evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.

Quality

79%

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SecuritybySnyk

Passed

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tessl review fix ./skills/skills-codex/result-to-claim/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%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.

A well-sequenced, highly actionable gate skill whose workflow clarity and fail-closed validation are exemplary. It is held back by duplicated caveat text, inline routing boilerplate, pseudocode mixed into Step 5, and a ~50-line wiki script inlined in SKILL.md rather than externalized.

Suggestions

Externalize the Step 5 wiki-update shell block into a reference file (e.g. references/wiki-update.md) or script, keeping only the decision rules inline — the ~50-line block is the main reason progressive_disclosure scores mid-scale.

Deduplicate the same-family/provisional acceptance caveat: state it once (e.g., in the evidence-precheck section) and remove the repeated 'Codex assurance' blockquote, which pads the top of the skill.

Replace the pseudocode in Step 5 ('if [ "$EXP_NODE_OK" = 1 ]:' with a colon, 'for each claim resolved by this verdict:') with real bash or an explicit instruction list so the wiki update is copy-paste executable like Steps 1.5–2.

DimensionReasoningScore

Conciseness

The body is operationally dense with no explanation of concepts Claude already knows, but the same-family/provisional acceptance caveat is stated twice (the 'Codex assurance' blockquote and again after Step 1.5), the reviewer-routing blockquotes read like accreted patch notes, and Step 5 embeds ~50 lines of shell inline — more than minor trimming is possible.

3 / 5

Actionability

Mostly executable guidance: exact wandb API call, ssh tail command, complete evidence_check resolver script, a full spawn_agent prompt template, and concrete research_wiki.py invocations. Not fully copy-paste ready because Step 5 mixes real commands with pseudocode ('if [ "$EXP_NODE_OK" = 1 ]:' colon syntax, 'for each claim resolved by this verdict:') and <placeholder> arguments.

4 / 5

Workflow Clarity

Steps 1 through 5 (including 1.5 and 3.5) are clearly sequenced with explicit validation checkpoints: a deterministic evidence pre-check, integrity-audit fail/warn handling that forces confidence to low, a fail-closed reviewer fallback with traced BLOCKED records, and feedback loops (low confidence → add experiments; repeated partial → narrow scope or pivot).

5 / 5

Progressive Disclosure

Section structure is clear and references are one level deep and clearly signaled ([evidence-precheck.md](../shared-references/evidence-precheck.md), review-tracing.md), but no bundle files exist here, the ../shared-references/ targets are absent from the bundle, and large content that belongs in reference files — the Step 5 wiki script and the routing-policy blockquotes — is inlined.

3 / 5

Total

15

/

20

Passed

Description

83%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.

A strong description that explicitly covers what the skill does and when to use it, in third-person voice, with concrete trigger phrases and a specific action list. Its main limitation is trigger breadth within the research-pipeline context rather than any vagueness.

DimensionReasoningScore

Specificity

Lists several concrete actions ('judge what claims the results support, what they don't, and what evidence is still missing', 'evaluates results against intended claims', 'routes to next action (pivot, supplement, or confirm)'), but omits result collection, verdict recording, and tracing, so coverage has minor gaps rather than being comprehensive.

4 / 5

Completeness

Explicitly answers both questions with concrete trigger phrases: what ('judge what claims the results support... A secondary Codex agent evaluates results against intended claims and routes to next action') and when ('Use when experiments complete... Use after experiments finish — before writing the paper or running ablations').

5 / 5

Trigger Term Quality

Good natural keyword coverage including a synonym pair ('Use when experiments complete' / 'Use after experiments finish') plus 'results', 'claims', 'evidence', 'before writing the paper', and 'ablations'; a few common user phrasings like 'analyze/interpret results' or 'wandb' are missing, so it falls short of the comprehensive-with-synonyms-and-extensions anchor.

4 / 5

Distinctiveness Conflict Risk

Result-to-claim adjudication is a clear niche with mostly distinct triggers, but 'when experiments complete' is broad within a research-pipeline suite and could overlap with closely related skills such as ablation planning or experiment auditing.

4 / 5

Total

17

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 2 suspicious

Warning

Total

13

/

16

Passed

Repository

wanshuiyin/Auto-claude-code-research-in-sleep

Path

skills/skills-codex/result-to-claim/SKILL.md

Reviewed

Table of Contents

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