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memory-to-skill

Turn workflows from your MemSearch memory into reusable skills. Use when the user asks to make/create/extract/distill a skill from what they just did or from past work, review skill candidates, install a distilled skill, or 'turn this into a skill'. Manages MemSearch procedural-memory candidates under .memsearch/skill-candidates/, not the host agent's own skills system.

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is memory-to-skill in zilliztech/memsearch

SKILL.md
Quality
Evals
Security

Quality

Content

85%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-engineered instruction skill: routing table up front, executable memsearch commands throughout, explicit human-in-the-loop validation at every irreversible step, and a clean split of platform-specific detail into verified one-level-deep references. The only deductions are minor: a repeated platform-reference pointer that could be stated once, and section C's transcript-drill command being delegated to another skill's reference instead of being written out.

Suggestions

In section C, inline at least one concrete form of the transcript-drill command (or a canonical example invocation) instead of deferring entirely to the memory-recall skill's platform reference, so the workflow is executable without a second lookup.

State the platform-reference pointer once (e.g., in the existing reference list near the top) and refer to it by short name from sections B, D, and Install paths, rather than repeating 'see your platform reference file' three times.

Compress section A's 'Be exact — do not guess' prose into a short checklist (verify against transcript / keep step general / never fabricate) to save tokens without losing the instruction.

DimensionReasoningScore

Conciseness

The body is dense and imperative with almost no generic explanation of concepts Claude already knows — everything is MemSearch-specific. Minor trimmable fat remains: 'see your platform reference file' is repeated in sections B, D, and Install paths, and the 'Be exact — do not guess' paragraph in A is wordier than a compact checklist would be. Not 5: a few sentences could be tightened without losing meaning; not 3: there is no padded or redundant explanation block.

4 / 5

Actionability

Nearly all guidance is copy-paste executable: 'printf ... | memsearch skills add --name ... --body-file -', 'memsearch skills status', 'git -C .memsearch/skill-candidates log --oneline -5', and the config get/set commands with defaults shown. The one real gap is section C's key step: 'Run the transcript drill (see the memory-recall skill's platform reference for the exact command)' delegates the exact command rather than stating it. Not 5: a central command of workflow C is not written out; not 3: every other workflow has complete, concrete commands with flags and expected outputs explained.

4 / 5

Workflow Clarity

Stages are explicitly labeled (0→1→2) with intent routing up front, and each flow carries explicit validation checkpoints and feedback loops: 'Before recommending or installing, skim the candidate's body... this is the last chance to catch a wrong step', 'skills status' hash comparison to detect drift, the interactive install checkpoint with confirmed destination, and the empty-list fallback offering A/C/D. Not 4: verification is explicit and repeated at every irreversible step (install, config set), plus a Guardrails checklist.

5 / 5

Progressive Disclosure

The body is a ~135-line overview and all five bundle files (references/claude-code.md, codex.md, openclaw.md, opencode.md, dsh.md) exist and are cited by exact relative path at the point of need, one level deep. Platform-specific config prefixes and install paths are correctly split out of the main body with clear signaling. Not 4: every reference is well-signaled, shallow, and verified against the actual bundle structure.

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.

This is a model description: it states what the skill does, gives explicit multi-trigger 'Use when' guidance including a verbatim user phrase, names the concrete store path, and explicitly disambiguates itself from the host agent's built-in skills system. All four dimensions land on the top anchors without padding or over-claiming.

DimensionReasoningScore

Specificity

Multiple concrete, third-person actions are listed with full coverage of the lifecycle: 'Turn workflows from your MemSearch memory into reusable skills', 'review skill candidates, install a distilled skill', and 'Manages MemSearch procedural-memory candidates under .memsearch/skill-candidates/' — a concrete store path is even named. Not 4: coverage spans create/distill/review/install with no missing major action.

5 / 5

Completeness

Explicitly answers both what ('Turn workflows from your MemSearch memory into reusable skills... Manages MemSearch procedural-memory candidates under .memsearch/skill-candidates/') and when ('Use when the user asks to make/create/extract/distill a skill... review skill candidates, install a distilled skill'). Not 4: the 'when' clause is concrete and multi-triggered, not merely present.

5 / 5

Trigger Term Quality

Comprehensive natural terms including synonyms users would actually type: 'make/create/extract/distill a skill', 'from what they just did', 'review skill candidates', and the verbatim quoted phrase "turn this into a skill". Not 4: it includes both the synonyms and the literal user phrasing, leaving no common variation missing.

5 / 5

Distinctiveness Conflict Risk

Clear niche with distinct triggers: MemSearch memory, .memsearch/skill-candidates/, and an explicit boundary statement ('not the host agent's own skills system') that prevents overlap with generic skill-authoring requests. Not 4: the disambiguation is explicit rather than implied.

5 / 5

Total

20

/

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

zilliztech/memsearch

Path

plugins/codex/skills/memory-to-skill/SKILL.md

Reviewed

Table of Contents

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