query

Search the FPF knowledge base and display hypothesis details with assurance information

Quality

41%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./plugins/fpf/skills/query/SKILL.md

Quality

Discovery

32%

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 identifies a specific domain (FPF knowledge base) and mentions key concepts (hypothesis, assurance), but it is too terse and lacks a 'Use when...' clause to guide skill selection. The domain-specific terminology may not align with how users naturally phrase their requests, and the description would benefit from expanded action details and explicit trigger guidance.

Suggestions

Add a 'Use when...' clause specifying trigger scenarios, e.g., 'Use when the user asks about FPF hypotheses, assurance levels, or needs to look up entries in the FPF knowledge base.'

Expand the description with more concrete actions and natural trigger terms, e.g., 'Searches the FPF knowledge base for hypotheses, displays assurance ratings and evidence details. Use when the user mentions FPF, hypothesis lookup, assurance information, or knowledge base queries.'

Clarify what 'FPF' stands for and what 'assurance information' entails to improve both specificity and trigger term coverage for users who may use different terminology.

Dimension	Reasoning	Score
Specificity	Names a domain ('FPF knowledge base') and two actions ('search' and 'display hypothesis details with assurance information'), but lacks comprehensive listing of concrete actions or capabilities.	2 / 3
Completeness	Describes what the skill does (search and display), but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2, and the 'what' is also weak, so score is 1.	1 / 3
Trigger Term Quality	Includes some relevant terms like 'FPF knowledge base', 'hypothesis', and 'assurance', but these are domain-specific jargon that may not match natural user language. Missing common variations or natural phrasing a user might use.	2 / 3
Distinctiveness Conflict Risk	'FPF knowledge base' is a specific domain reference that provides some distinctiveness, but without clearer trigger terms or context, it could overlap with other knowledge base search skills.	2 / 3
	Total	7 / 12 Passed

Implementation

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill clearly communicates the FPF knowledge base query workflow and provides good output format examples, but suffers from redundancy across sections and lacks concrete implementation details for the actual search mechanism. The skill would benefit from consolidating overlapping examples and adding specifics about how to parse hypothesis files and handle edge cases.

Suggestions

Add concrete implementation details for the search mechanism — specify how to read/parse hypothesis files (e.g., YAML frontmatter parsing, grep commands, or file glob patterns) rather than just saying 'search .fpf/knowledge/'

Consolidate the Output Format, R_eff Display, Dependency Tree Display, and Examples sections to eliminate redundancy — the redis-caching example appears in at least 3 places with overlapping information

Add error handling guidance: what to do when hypothesis files are malformed, R_eff is missing from L1+ files, or dependency references point to non-existent hypotheses

Consider splitting detailed output format templates into a separate reference file to keep the main SKILL.md focused on the search workflow

Dimension	Reasoning	Score
Conciseness	The skill is moderately efficient but has significant redundancy — the output format section, examples section, and search methods section all show overlapping information (e.g., redis-caching details appear multiple times). The R_eff display and dependency tree sections repeat what's already shown in the output format.	2 / 3
Actionability	The skill provides clear output format examples and search patterns, but the actual implementation is vague — it says 'search .fpf/knowledge/' without specifying how (grep? glob? read YAML frontmatter?). The slash-command syntax (/fpf:query) is shown but there's no executable code for performing the search, parsing hypothesis files, or computing R_eff.	2 / 3
Workflow Clarity	The 3-step action sequence is clear at a high level (search → display details → present in table), but lacks validation checkpoints — what happens if a hypothesis file is malformed, if R_eff is missing from an L1+ file, or if dependencies reference non-existent hypotheses? No error handling or fallback behavior is specified.	2 / 3
Progressive Disclosure	The content is reasonably structured with clear sections and tables, but it's somewhat monolithic at ~130 lines with no references to external files. The output format, R_eff display, dependency tree display, and examples sections could be consolidated or split out, as they contain overlapping content that inflates the document.	2 / 3
	Total	8 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: NeoLabHQ/context-engineering-kit
Commit: dedca19

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

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