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query

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

42

Quality

41%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./plugins/fpf/skills/query/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

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

This skill provides a comprehensive description of how to query an FPF knowledge base with good output format examples and multiple search patterns. However, it suffers from redundancy across sections (the same redis-caching example appears in multiple places), lacks concrete implementation details for how to actually search and parse files, and misses error handling/validation for edge cases like missing files or malformed data.

Suggestions

Add concrete implementation details for searching: specify file format (YAML frontmatter?), how to parse hypothesis files, and what tools/commands to use for searching (e.g., grep, file reading patterns)

Consolidate redundant examples — the redis-caching hypothesis appears in Output Format, Examples, and R_eff Display sections; show it once in Output Format and reference it elsewhere

Add error handling guidance: what to display when no results match, when a hypothesis file is malformed, or when referenced evidence files are missing

Consider splitting the detailed output format templates and dependency tree legend into a reference file to keep the main skill focused on the search workflow

DimensionReasoningScore

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 '/fpf:query' commands suggest a slash-command interface but no implementation details are given for how to actually perform the search or parse hypothesis files.

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 no results are found? What if a hypothesis file is malformed? The conditional logic (if layer >= L1, if has dependencies) is mentioned but not structured as a clear decision tree.

2 / 3

Progressive Disclosure

The content is reasonably well-organized with clear sections, but it's quite long (~150 lines) with no references to external files despite the bundle having none. The output format, R_eff display, dependency tree display, and examples sections could be consolidated or split into reference files to reduce the main skill's length.

2 / 3

Total

8

/

12

Passed

Description

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 searching and displaying hypothesis details, but it lacks a 'Use when...' clause, does not expand the FPF acronym, and provides limited natural trigger terms. It would benefit significantly from explicit trigger guidance and more concrete action descriptions.

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 'FPF' acronym and include natural language variations users might use to refer to this knowledge base.

List more specific concrete actions beyond 'search' and 'display', such as 'retrieve hypothesis summaries, show assurance scores, list related evidence.'

DimensionReasoningScore

Specificity

It names a domain ('FPF knowledge base') and two actions ('search' and 'display hypothesis details with assurance information'), but these are not comprehensively listed concrete actions—'display hypothesis details with assurance information' is somewhat vague about what specific operations are performed.

2 / 3

Completeness

It describes what the skill does (search and display), but there is no 'Use when...' clause or equivalent explicit trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' portion is also weak, so this scores a 1.

1 / 3

Trigger Term Quality

It includes some relevant keywords like 'FPF', 'knowledge base', 'hypothesis', and 'assurance', but these are fairly domain-specific jargon. It lacks natural language variations a user might say, and 'FPF' is an unexpanded acronym that may not match user queries.

2 / 3

Distinctiveness Conflict Risk

The mention of 'FPF knowledge base' and 'hypothesis details with assurance information' provides some domain specificity, but without clearer triggers or expanded terminology, it could overlap with other knowledge base search skills.

2 / 3

Total

7

/

12

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
NeoLabHQ/context-engineering-kit
Reviewed

Table of Contents

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