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memory-recall

Search and recall relevant memories from past sessions via MemSearch. Use for past decisions, debugging notes, previous conversations, and project knowledge, especially when the context includes a MemSearch memory hint. Skip purely current-code questions or when the user asks to ignore memory.

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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 a dense, highly actionable workflow: concrete tool calls with specific parameters, relevance checkpoints, and failure-mode diagnostics. The main deductions are inline time-sensitive version constraints that belong in a compatibility/deprecated note or referenced file, and a single external reference that leaves the skill's own bundle.

Suggestions

Move the version compatibility details (V1 pin, plugin 0.4.0 range, OpenCode >=2.0.32 <3) into a 'Compatibility' or deprecated-patterns section, or into the referenced diagnostics file, to reduce inline time-sensitive content.

Fold the unclear-query and capture-pending fallbacks into the numbered step sequence (e.g., a step 0 or explicit sub-step) so the main workflow reads as one linear flow.

Verify the `../memory-config/references/opencode.md` link resolves from this skill's installed location, or move the diagnostics content into this skill's own references/ directory.

DimensionReasoningScore

Conciseness

The body is mostly lean and assumes competence, but the trailing paragraph carries time-sensitive version data ("V1 users pin the published `@zilliz/memsearch-opencode@0.3.17`. Plugin 0.4.0 supports OpenCode >=2.0.32 <3") that is not placed in a deprecated or compatibility section, which the guidelines explicitly penalize. This matches anchor 3 (mostly efficient with some content that could be tightened or relocated).

3 / 5

Actionability

Guidance is fully concrete with exact tool names and parameter values: "Use `memory_search` with a concrete query and `top_k: 5`", "Use `memory_get` with the most promising `chunk_hash` values", and "use `memory_transcript` with `session_id`, `turn_id` and `db_path`... Set `context: 3`; for an anchor without a turn, use `limit: 10`", covering both common and edge cases. This matches anchor 5 for an instruction-only skill with executable-grade specificity.

5 / 5

Workflow Clarity

A clear numbered 1-4 sequence with explicit checkpoints ("Evaluate relevance before expanding results", "inspect its text before selecting hashes") and an error-recovery branch for transcript lookup failures. It stops short of anchor 5 because the fallback behaviors (unclear query, capture-pending) sit outside the numbered flow, slightly blurring the main sequence.

4 / 5

Progressive Disclosure

The skill is under 50 lines, organized under a clear ## Steps section, with exactly one well-signaled reference whose purpose and sharing are stated ("See [OpenCode diagnostics](../memory-config/references/opencode.md), also used by `memory-config`"). It falls short of anchor 5 because that single reference points outside the skill's own bundle (no references/ directory exists here), making it unverifiable and creating a cross-bundle dependency.

4 / 5

Total

16

/

20

Passed

Description

82%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 states what the skill does, gives natural trigger terms with an explicit 'Use for' clause, and even includes skip guidance to avoid false triggers. The only weakness is that it summarizes capabilities at a high level (search/recall) rather than enumerating the concrete actions the skill performs.

Suggestions

Enumerate the concrete capabilities in the description, e.g., "search memory chunks, expand them to full Markdown sections, and pull verified transcript excerpts" to lift specificity.

Add one or two common user synonyms such as 'remember' or 'recall what we previously decided' to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

"Search and recall relevant memories from past sessions via MemSearch" names the domain plus 1-2 concrete actions, matching the anchor-3 pattern ("Processes PDF files and extracts content"). It does not list several distinct actions (e.g., expanding memory chunks or transcript lookup), so it falls below anchor 4.

3 / 5

Completeness

It explicitly answers what ("Search and recall relevant memories from past sessions via MemSearch") and when ("Use for past decisions, debugging notes, previous conversations, and project knowledge, especially when the context includes a MemSearch memory hint") with concrete trigger phrases, plus explicit skip conditions. This matches anchor 5 exactly.

5 / 5

Trigger Term Quality

Natural phrases like "past decisions", "debugging notes", "previous conversations", "project knowledge", and "MemSearch memory hint" give good keyword coverage. Common synonyms users might say ("remember", "what we decided last time") are missing, keeping it below anchor 5.

4 / 5

Distinctiveness Conflict Risk

A clear niche (MemSearch memory recall) with a distinct trigger ("MemSearch memory hint") and explicit anti-triggers ("Skip purely current-code questions or when the user asks to ignore memory") minimizes conflict with other skills, matching anchor 5.

5 / 5

Total

17

/

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

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository

zilliztech/memsearch

Path

plugins/opencode/skills/memory-recall/SKILL.md

Reviewed

Table of Contents

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