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agent-memory-mcp

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

52

Quality

58%

Does it follow best practices?

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SecuritybySnyk

Critical

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

Quality

Content

67%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 well-structured, largely executable runbook: pinned-revision review with a user-approval gate, concrete install/start commands, and documented MCP tool interfaces. Its main weaknesses are the circular "When to Use" filler, generic Limitations boilerplate, and the absence of any failure-recovery guidance around the install and server-start steps.

Suggestions

Replace the circular "When to Use" sentence with concrete invocation conditions (e.g., "Use when the user asks to save, recall, or search project knowledge across sessions").

Trim the boilerplate Limitations lines and keep only skill-specific caveats (e.g., the commit-pin trust note and Node v18+ requirement).

Add brief failure-recovery guidance for the install/start steps (e.g., what to check if `npm ci` or `npm run compile` fails, or how to verify the MCP server is reachable before using the tools).

DimensionReasoningScore

Conciseness

The setup and tool sections are lean and command-driven, but the body carries filler: "This skill is applicable to execute the workflow or actions described in the overview" is circular padding, and parts of the Limitations section ("Do not treat the output as a substitute for environment-specific validation, testing, or expert review") read as boilerplate. This matches anchor 3 ("mostly efficient but includes some unnecessary explanation or could be tightened") better than 4, where only minor trim instances would remain.

3 / 5

Actionability

The setup gives concrete, executable commands — a pinned git clone with commit hash, `npm ci`, `npm run compile`, and `npm run start-server my-project $(pwd)` — and each MCP tool documents args with a usage example. It falls short of 5 because of unresolved placeholders (`<approved-agent-memory-directory>`, `<project_id>`, `<absolute_path_to_target_workspace>` in the primary command) and no example payload for `memory_write` content.

4 / 5

Workflow Clarity

The three-step setup (review pinned revision → install approved tree → start server) is clearly sequenced with an explicit checkpoint ("Show the findings and exact commit, then wait for explicit user approval") and a re-review guard on changing the pin. It is not a 5 because there is no error-recovery feedback loop for the install/start steps (e.g., what to do if `npm ci` or `npm run compile` fails).

4 / 5

Progressive Disclosure

The body (~96 lines) is well-organized into distinct sections (Prerequisites, Setup, Capabilities, Dashboard, Limitations) with no bundled reference files to disclose; the inline MCP tool reference is short enough to belong in SKILL.md. It is not a 5 because the ~30-line tool catalog and dashboard section could be split out, and there are no signaled references for deeper material even though the skill points to an external repository.

4 / 5

Total

15

/

20

Passed

Description

48%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 communicates a clear domain and niche but stops there: it states no concrete capabilities and gives no guidance on when to invoke the skill. Adding an explicit "Use when..." clause and naming the actual operations (e.g., storing, searching, and retrieving memories) would materially improve it.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user wants to persist, recall, or search long-term knowledge (architecture decisions, patterns, past fixes) across sessions."

Replace the generic "provides persistent, searchable knowledge management" with the concrete operations the MCP server exposes, e.g. "Stores, searches, and retrieves typed memories (architecture, patterns, decisions) via an MCP server."

Include natural user phrasings/synonyms such as "remember this", "knowledge base", or "past decisions" so the skill triggers on how users actually ask for memory.

DimensionReasoningScore

Specificity

The description names its domain ("persistent, searchable knowledge management for AI agents") but the only action verb is "provides", which is generic; no concrete operations like storing, searching, or retrieving memories are stated. It sits between anchor 2 ("Names the domain but actions are minimal or generic") and anchor 3 (which requires 1-2 explicitly concrete actions), and since "searchable" is an attribute rather than a stated action, anchor 2 is the closer fit.

2 / 5

Completeness

The "what" is reasonably clear (a persistent, searchable memory system for agents), but there is no "when" guidance at all — no "Use when..." clause or equivalent trigger phrasing, which caps completeness at 3 per the judging guidelines. It is not a 2 because the "what" is concrete and specific rather than vague.

3 / 5

Trigger Term Quality

It contains some relevant keywords ("memory system", "knowledge management", "Architecture, Patterns, Decisions") but misses natural phrases users would say such as "remember this", "knowledge base", or "recall past decisions". Not generic enough for 2, but the missing variations and synonyms keep it below 4.

3 / 5

Distinctiveness Conflict Risk

"Hybrid memory system" scoped to "AI agents (Architecture, Patterns, Decisions)" carves out a fairly distinct niche with minimal overlap risk against unrelated skills. It is not a 5 because it could still overlap with other agent-memory or knowledge-base skills given the absence of distinct trigger phrases.

4 / 5

Total

12

/

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
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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