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agent-memory-discipline

Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

Quality

78%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/antigravity-agent-memory-discipline/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

81%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 instruction skill with an explicit six-step workflow, concrete templates, and strong error-recovery guidance throughout. The main weaknesses are repetition across the Steps, Best Practices, and Examples sections, and duplication between the body and references/entry-format.md that inflates token cost without adding information.

Suggestions

Remove the Best Practices Do/Don't list or fold it into the corresponding steps — it restates Steps 2–5 almost verbatim.

Keep the entry-format examples (pnpm template, closing format) only in references/entry-format.md and reference them from the Examples section instead of duplicating them in the body.

Trim the closing Mnemoverse paragraph and the final policy caveats, which restate points already covered in Security & Safety Notes and Limitations.

DimensionReasoningScore

Conciseness

The body is substantive and avoids explaining concepts Claude already knows, but has real structural repetition: the Best Practices section restates Steps 2–5 nearly verbatim, Example 1 duplicates the entry template already shown in "What Following This Skill Produces", and the closing paragraphs restate Security/Limitations caveats. This is more than the "minor over-explanation" of a 4, though not severely padded like a 2.

3 / 5

Actionability

For an instruction-only skill the guidance is fully concrete: explicit lists of recall triggers, save triggers, and do-not-save items; copy-paste ready entry templates in text blocks; exact suggested phrasings for surfacing contradictions; and a concrete search strategy ("the words the user actually used, plus the project or repository name"). Not below 5 because no key execution detail is left abstract.

5 / 5

Workflow Clarity

Steps 1–6 are clearly sequenced with explicit checkpoints and error-recovery loops: recall fallback (one broader query, then proceed without memory), contradiction handling (surface both with dates and ask), rejected-save handling (report once, do not rephrase in a loop), and per-step pitfalls. No destructive or batch operations apply, so no cap is triggered.

5 / 5

Progressive Disclosure

The single bundle reference (references/entry-format.md) is real, one level deep, and clearly signaled from Step 3/4 context, and sections are well organized. It falls short of 5 because the body duplicates entry-format examples that already live in the reference file, and the Examples section carries content that could itself be pushed to the reference.

4 / 5

Total

17

/

20

Passed

Description

66%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 specific about the skill's actions and occupies a distinct niche, with good natural keyword coverage. Its main weakness is the missing "Use when..." trigger clause — "Works with any memory backend" describes scope rather than invocation conditions, which caps completeness.

Suggestions

Add an explicit trigger clause, e.g. "Use when a memory tool or MCP memory server is connected, when the user says 'remember this' or 'what did we decide', or when the agent loses preferences and past decisions between sessions."

Include common natural variations users would say — "remember", "forgets", "loses preferences between sessions" — alongside the existing keywords.

Briefly mention the distinctive sub-behaviors (closing superseded entries, surfacing contradictions) to differentiate it further from general memory skills.

DimensionReasoningScore

Specificity

The description names several concrete actions — "recall from long-term memory before acting" and "save decisions, corrections and failures afterwards" — with the save categories explicitly enumerated. Not a 5 because the recall/save sub-behaviors (closing superseded entries, contradiction handling) are absent from the description itself.

4 / 5

Completeness

The "what" is clear (standing rules for when to recall and when to save), but there is no "Use when..." clause or equivalent trigger guidance — "Works with any memory backend" states scope, not when to invoke the skill. Per the rubric guideline, a missing explicit trigger caps completeness at 3.

3 / 5

Trigger Term Quality

Natural terms like "long-term memory", "recall", "save", and "memory backend" are present, which users discussing memory would plausibly say. A few natural variations ("remember this", "forgets between sessions", "preferences") are missing, keeping it below 5.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (usage discipline for memory, not backend setup), distinct from most skills. Minor overlap risk remains with closely related memory-architecture or context-engineering skills, and the absence of explicit triggers makes it slightly less distinguishable than a 5.

4 / 5

Total

15

/

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

boisenoise/skills-collections

Path

skills/antigravity-agent-memory-discipline/SKILL.md

Reviewed

Table of Contents

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