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learning-loop

Capture new learnings discovered during code exploration or user interaction that were not present in context, memories, or codebase documentation. This skill should be invoked when Claude discovers something new about the codebase, tools, workflows, or domain knowledge that could benefit future sessions.

65

Quality

77%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/learning-loop/SKILL.md

The canonical home for this skill is learning-loop in cteyton/packmind

SKILL.md
Quality
Evals
Security

Quality

Content

92%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 well-structured, concise, and fully actionable, providing an executable script with arguments, examples, and output format. The only minor weakness is mild redundancy across the three example invocations.

DimensionReasoningScore

Conciseness

The body is mostly lean and avoids explaining concepts Claude already knows, but the three near-identical example invocations add mild redundancy that could be trimmed.

4 / 5

Actionability

It gives a fully executable, copy-paste-ready command, a concrete argument table, three realistic example summaries, and shows the exact output YAML format.

5 / 5

Workflow Clarity

This is a simple single-action skill whose one action (run the logging script) is unambiguous, and the script itself performs the validation (empty-arg check, .claude lookup), so the simple-skill exception applies and no destructive/batch cap is triggered.

5 / 5

Progressive Disclosure

Content is well-organized into clear sections and delegates execution to a single one-level-deep, well-signaled bundle file (scripts/log-learning.sh) that exists and is referenced by its real path.

5 / 5

Total

19

/

20

Passed

Description

62%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 in clear third-person voice and covers both what the skill does and when to invoke it, but it describes a single broad action rather than multiple concrete ones and lacks the most natural user-spoken trigger phrases. It is solid but could be sharpened with explicit 'Use when...' trigger wording and more specific capability verbs.

Suggestions

Add an explicit 'Use when...' clause with concrete trigger phrases a user would naturally say (e.g., 'Use when you discover undocumented behavior, hidden config, or a workflow pattern not in CLAUDE.md').

Replace the single generic verb 'Capture' with a few concrete actions (e.g., 'Log, timestamp, and append new learnings to a shared learning file').

Add natural synonyms/keywords to broaden trigger matching (e.g., 'learnings', 'undocumented behavior', 'knowledge gaps', 'notes for future sessions').

DimensionReasoningScore

Specificity

The description names the domain ('Capture new learnings discovered during code exploration or user interaction') but lists essentially one concrete action rather than multiple specific actions, leaving coverage incomplete.

3 / 5

Completeness

It answers both what ('Capture new learnings...') and when ('This skill should be invoked when Claude discovers something new...'), but the when could be more explicit with concrete user-facing trigger phrases.

4 / 5

Trigger Term Quality

Relevant terms like 'code exploration', 'user interaction', 'codebase, tools, workflows, or domain knowledge' appear, but common natural trigger phrasings and synonyms a user would actually say are missing.

3 / 5

Distinctiveness Conflict Risk

The 'capture new learnings discovered... not present in context, memories, or codebase documentation' framing carves a fairly distinct niche, with only minor overlap risk against general memory/context skills.

4 / 5

Total

14

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
cteyton/packmind
Reviewed

Table of Contents

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