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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

88%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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-structured, actionable skill body with strong progressive disclosure: platform detail is correctly split into five real reference files, and the workflows include genuine validation checkpoints and error-recovery fallbacks. The main weaknesses are a subtly broken printf example in section A, some repeated platform-pointer prose, and no post-install verification step.

Suggestions

Fix the section A snippet: `printf '%s'` does not interpret `\n` in its argument, so the piped body contains literal backslash-n. Use a quoted heredoc instead, e.g. `memsearch skills add --name "<slug>" --description "..." --body-file - <<'EOF'`.

State the platform-reference location once (the intro list) and drop the three later "see your platform reference file" repetitions in B, D, and Install paths to save tokens.

Add a post-install verification step in section B (e.g. re-run `memsearch skills status` or check the installed path) so the install flow closes with an explicit confirmation rather than only a restart reminder.

DimensionReasoningScore

Conciseness

Mostly efficient and domain-specific (MemSearch's memory layers and skills status semantics are genuinely unknown to Claude), but the platform-reference pointer is repeated four times (intro list, "Replace <platform> with your platform key prefix (see the reference file)", "See your platform reference file for the exact...commands", "See your platform reference file for the platform-specific skill directory") and concepts like the git-tracked store are restated, so it sits at anchor 4 rather than 5.

4 / 5

Actionability

Concrete, specific commands throughout — "memsearch skills status", "memsearch skills list", "memsearch skills install <name> --path <...>", real config keys like "plugins.<platform>.memory_to_skill.min_occurrences". However the flagship snippet "printf '%s' \"## <title>\\n\\n1. ...\" | memsearch skills add ... --body-file -" is not copy-paste ready: printf '%s' does not interpret \n in its argument, so the piped body would contain literal backslash-n instead of newlines. That keeps it below anchor 5.

4 / 5

Workflow Clarity

Each route (A/B/C/D) has a clear sequence with real checkpoints: "installing copies the candidate as-is, so this is the last chance to catch a wrong step", an interactive confirm-destination gate, "Only if that command fails (unknown format) fall back to reading the raw file directly", and "never fabricate". Minor gaps keep it at 4: section A's flow is prose rather than numbered steps, and there is no post-install verification that the skill landed (only a reminder to restart).

4 / 5

Progressive Disclosure

The body is a clear overview that keeps platform-specific detail out of SKILL.md behind well-signaled, one-level-deep references; all five files named in the body (references/claude-code.md, codex.md, openclaw.md, opencode.md, dsh.md) exist in the bundle, matching the platform list exactly.

5 / 5

Total

17

/

20

Passed

Description

95%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: it names concrete actions, states a clear scope with an explicit storage path, and gives an explicit 'Use when' clause enumerating verb synonyms plus a quoted natural user phrase. The only gap is that the configure intent covered by the body is absent, which keeps specificity just below comprehensive.

DimensionReasoningScore

Specificity

Lists several concrete actions — "Turn workflows from your MemSearch memory into reusable skills", "review skill candidates", "install a distilled skill", "Manages MemSearch procedural-memory candidates under .memsearch/skill-candidates/" — with a concrete path. It falls just short of anchor 5 because the configure capability (section D of the body: enable/min_occurrences/paths) is not mentioned, a minor coverage gap.

4 / 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... or 'turn this into a skill'") with concrete trigger phrases.

5 / 5

Trigger Term Quality

"make/create/extract/distill a skill", "from what they just did or from past work", "review skill candidates", "install a distilled skill", plus the quoted natural user utterance "'turn this into a skill'" — comprehensive coverage of natural terms with verb synonyms and an exact phrase a user would type.

5 / 5

Distinctiveness Conflict Risk

Clear MemSearch-specific niche with distinct triggers, and it explicitly disambiguates from the nearest conflict — "not the host agent's own skills system" — minimizing wrong-skill triggering.

5 / 5

Total

19

/

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

zilliztech/memsearch

Path

plugins/claude-code/skills/memory-to-skill/SKILL.md

Reviewed

Table of Contents

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