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reflect

Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes. Use after user corrections ("no", "wrong"), praise ("perfect", "exactly"), or when discovering edge cases. Complements .squad/agents/{agent}/history.md and .squad/decisions.md.

Quality

77%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./.github/skills/reflect/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 delivers a clear, actionable four-phase workflow with concrete detection patterns, thresholds, and worked examples. Its main costs are token redundancy (duplicated trigger/example content) and an undefined user-rejection path in the approval loop.

Suggestions

Cut the redundant 'When to Use' section (it restates the Triggers tables almost verbatim) and drop the decorative ASCII box in Phase 3 in favor of a plain output template — this is the lowest-scoring dimension (conciseness).

Merge the two Usage Examples into Phase 2's existing examples rather than repeating them, or move all worked examples into a references/ file and keep one inline.

Define the post-approval branches: what to do when the user answers 'n' or 'edit' at the 'Apply changes?' prompt, and add a session-end review step to the Process matching the one promised in the Workflow section.

DimensionReasoningScore

Conciseness

The body avoids explaining concepts Claude already knows, but contains real redundancy: the 'When to Use' section restates the Triggers tables nearly verbatim, the Usage Examples restate Phase 2's detection examples, and the ASCII box in Phase 3 is decorative padding. This is 'mostly efficient but could be tightened' rather than the minor-trimming of anchor 4.

3 / 5

Actionability

Concrete, specific guidance throughout: exact detection patterns ("Explicit rejection: 'no', 'not like that'"), a precise confidence-threshold table, an output template, and two fully worked conversation-to-output examples. Falls short of anchor 5 because persistence targets are described abstractly ("governed runtime memory", "tracked governing source") without file- or command-level specifics.

4 / 5

Workflow Clarity

Phases 1-4 are clearly sequenced with an explicit validation gate ("ALWAYS show changes before applying", "Apply changes? [Y/n/edit]") and explicit skip thresholds, so the destructive-operation cap does not apply. Not anchor 5 because the reject/edit path after the approval prompt is undefined and the session-end review mentioned in the workflow has no corresponding process step — minor validation gaps.

4 / 5

Progressive Disclosure

A single well-organized SKILL.md with clear headed sections and a 'See Also' pointer list; no bundle files exist so nothing is misnested. Minor gap: at ~220 lines, the detailed trigger tables and worked examples could plausibly live in a reference file, fitting 'good structure; minor organization gaps' rather than the cleanly-split anchor 5.

4 / 5

Total

15

/

20

Passed

Description

78%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 both what the skill does and when to use it, with naturally quotable trigger phrases. Its main gaps are limited action enumeration and trigger words so common they risk over-triggering.

DimensionReasoningScore

Specificity

Names the domain and one concrete action ("extracts HIGH/MED/LOW confidence patterns from conversations") plus a purpose ("prevent repeating mistakes"), but does not list several distinct actions, matching the '1-2 concrete actions, not comprehensive' anchor. It is not score 2 because the action named is specific rather than generic, and not score 4 because there is no enumeration of multiple concrete capabilities.

3 / 5

Completeness

Clearly answers both: what it does ("extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes") and when to use it with concrete trigger phrases ("Use after user corrections ('no', 'wrong'), praise ('perfect', 'exactly'), or when discovering edge cases"), exactly matching the top anchor.

5 / 5

Trigger Term Quality

Good keyword coverage with natural quoted utterances users actually say ("no", "wrong", "perfect", "exactly") plus terms like "user corrections", "praise", and "edge cases". A few common variants are missing (e.g., "great", "not like that", "never do"), so it falls short of the comprehensive-synonyms anchor 5.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (conversation-derived learning capture) distinct from other skills, but its trigger words are extremely common everyday utterances, creating minor risk of firing on ordinary exchanges. This is 'mostly distinct; minor overlap risk' rather than the minimal-conflict anchor 5.

4 / 5

Total

16

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository

bradygaster/squad

Path

.github/skills/reflect/SKILL.md

Reviewed

Table of Contents

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