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memory-recall

Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this before'. Also use when you see `[memsearch] Memory available` hints injected via SessionStart or UserPromptSubmit. Typical flow: search for 3-5 chunks, expand the most relevant, optionally deep-drill into original transcripts via the anchor format. Skip when the question is purely about current code state (use Read/Grep), ephemeral (today's task only), or the user has explicitly asked to ignore memory.

74

Quality

93%

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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 content is highly actionable and well-structured for a simple retrieval skill, with executable commands and a clear workflow. Minor verbosity in the inline bash derivation snippets is the only thing holding it back from top marks.

Suggestions

Move the dynamic-collection derivation bash into the referenced derive-collection.sh and inline only a short call, reducing noise at the top of the body.

Add an explicit validation/checkpoint note after the search step (e.g., "if results are empty or off-topic, reformulate the query") to strengthen the feedback loop.

Condense the three similar exploration one-liners in "When unsure what to search" into a single parameterized example to save tokens.

DimensionReasoningScore

Conciseness

The body is largely lean and assumes Claude's competence, but the inline dynamic-collection bash one-liner and the three exploration one-liners in "When unsure" add noise that could be trimmed or factored out; not quite a 5.

4 / 5

Actionability

Provides fully executable, copy-paste-ready commands (memsearch search/expand with exact flags, transcript.py invocation) plus a concrete fallback (uvx memsearch) and example bash snippets, covering the common cases.

5 / 5

Workflow Clarity

A clear numbered 1-5 sequence with an evaluation checkpoint (step 2) and a fallback exploration loop in "When unsure"; minor gaps in explicit validation/error-checkpoints beyond the memsearch-not-found case keep it just under 5.

4 / 5

Progressive Disclosure

A simple, single-purpose skill under 50 lines with well-organized sections (Project Collection, Your Task, Steps, When unsure, Output Format) and one-level-deep references to plugin scripts; structure is easy to navigate.

5 / 5

Total

18

/

20

Passed

Description

100%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 exemplary: third-person voice, concrete actions, rich natural trigger phrases, and explicit both-side guidance (when to use and when to skip). It clearly differentiates the skill from current-state tooling.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Search and recall relevant memories", "search for 3-5 chunks, expand the most relevant", and "deep-drill into original transcripts via the anchor format" — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both "what" (search and recall memories via memsearch) and "when" (a concrete "Use when..." clause with trigger phrases), and additionally provides negative triggers ("Skip when...") making the activation criteria unambiguous.

5 / 5

Trigger Term Quality

Includes natural user phrases ("what did I decide about X", "why did we do Y", "have I seen this before") plus synonyms (historical context, past decisions, debugging notes, previous conversations) and an injected-hint trigger, covering the full range of ways a user would signal this need.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (memory recall via memsearch) and is explicitly distinguished from current-state tools ("use Read/Grep"), minimizing overlap with other skills.

5 / 5

Total

20

/

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.

Validation15 / 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
zilliztech/memsearch
Reviewed

Table of Contents

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