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skill-lookup

Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components.

84

0.97x
Quality

81%

Does it follow best practices?

Impact

80%

0.97x

Average score across 3 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

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.

A well-structured, actionable skill body with concrete tool usage, parameters, examples, and an install verification step. Main weaknesses are mild cross-section redundancy and the absence of an error-recovery loop after verification.

Suggestions

Add a feedback loop to the install workflow: if reading back SKILL.md shows missing/broken frontmatter, re-save and re-verify before confirming success.

Deduplicate the overlap between the Workflow, Available Tools, and How-to sections — keep parameter detail in one place and let the Workflow reference it.

Show handling of get_skill's return (e.g., iterating the returned file list to write each file) so the install path is fully copy-paste executable.

DimensionReasoningScore

Conciseness

The body is lean and avoids explaining concepts Claude already knows, though the Workflow and Available Tools sections overlap with the later How-to sections, leaving minor redundancy that could be tightened.

4 / 5

Actionability

Provides concrete MCP tool names, parameters with defaults/limits, executable example calls, and explicit install paths, with only minor gaps such as absent return-value handling and no full install script.

4 / 5

Workflow Clarity

A clearly sequenced search→present→retrieve→install→confirm workflow includes an explicit verification checkpoint ("Read back SKILL.md to verify the frontmatter is intact"), but lacks an error-recovery feedback loop if verification fails.

4 / 5

Progressive Disclosure

No bundle files exist, so the single-file body is judged on structure; sections are well-organized with clear headers, with only minor overlap between the Workflow and How-to sections preventing a 5.

4 / 5

Total

16

/

20

Passed

Description

87%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, third-person description that concretely states both capability and activation triggers with good natural-language keywords. It is distinct and unlikely to misfire; the only minor gap is slightly broader action coverage.

DimensionReasoningScore

Specificity

Names the domain (Agent Skills registry via MCP) and three concrete actions — "Search, retrieve, and install" — giving good coverage, but stops short of the fully comprehensive action list needed for a 5.

4 / 5

Completeness

Explicitly answers what ("Search, retrieve, and install Agent Skills…using MCP tools") and when ("Use when the user asks to find skills, browse skill catalogs, install a skill…") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural phrases users would say ("find skills", "browse skill catalogs", "install a skill", "extend Claude's capabilities"), with only minor synonyms missing.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche — the prompts.chat skill registry via MCP tools — with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

18

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
f/awesome-chatgpt-prompts
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.