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speckit-analyze

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

75

1.47x
Quality

67%

Does it follow best practices?

Impact

90%

1.47x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/speckit-analyze/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

This is a well-crafted, highly actionable analysis skill with a clear multi-step workflow, explicit validation checkpoints, and concrete output formats. Its main weakness is length and some internal repetition—particularly the near-identical pre/post hook logic blocks—which inflates token cost without adding proportional value. The content would benefit from extracting repeated patterns into referenced files.

Suggestions

Extract the duplicated extension hook checking logic (pre and post) into a single referenced file or a reusable template section, referencing it from both steps to reduce ~40 lines of repetition.

Consider moving the detailed detection pass descriptions (Section 4 A-F) into a separate reference file, keeping only a summary list in the main skill body to improve progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is detailed and mostly necessary given the complexity of the multi-artifact analysis task, but there is significant repetition—the extension hook logic is duplicated nearly verbatim for pre- and post-hooks (Steps 0 and 9), and some sections like 'Operating Principles' restate constraints already covered in 'Operating Constraints'. The semantic model building instructions are appropriately detailed but could be tighter.

2 / 3

Actionability

The skill provides highly concrete, executable guidance: specific shell commands (check-prerequisites.sh with flags), exact file paths, explicit detection categories with examples of what to flag (vague adjectives, placeholders like TODO/TKTK/???), precise output table schemas with column headers, severity heuristics with clear definitions, and specific next-action command suggestions. The report format is copy-paste ready.

3 / 3

Workflow Clarity

The 9-step workflow is clearly sequenced with explicit prerequisites (abort if files missing), progressive loading, multiple detection passes, severity assignment, structured output, and a final remediation offer. Validation is built into the process—Step 1 checks prerequisites and aborts on failure, the read-only constraint prevents destructive operations, and the constitution alignment check serves as a critical validation gate.

3 / 3

Progressive Disclosure

The skill is a monolithic document (~200+ lines) with all content inline. While internally well-structured with clear headers, the duplicated hook-checking logic and the detailed detection pass descriptions could benefit from being split into referenced files. No bundle files are provided to offload complexity, and the skill doesn't reference any supporting documentation for its more complex subsystems (e.g., semantic model building, severity heuristics).

2 / 3

Total

10

/

12

Passed

Description

57%

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 clear and distinctive niche (cross-artifact consistency analysis for spec/plan/tasks files), which is its strongest aspect. However, it lacks an explicit 'Use when...' clause, relies on somewhat technical jargon rather than natural trigger terms, and doesn't enumerate the specific checks or outputs the skill performs.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks to review, validate, or check consistency between spec.md, plan.md, and tasks.md after generating tasks.'

List specific concrete actions the analysis performs, e.g., 'Checks for missing requirements coverage, detects contradictions between spec and plan, validates task completeness against the plan.'

Include natural trigger terms users might say, such as 'review tasks', 'validate plan', 'check spec alignment', or 'verify task coverage'.

DimensionReasoningScore

Specificity

It names the domain (cross-artifact consistency and quality analysis) and specifies the artifacts involved (spec.md, plan.md, tasks.md), but the actual concrete actions beyond 'analysis' are vague — it doesn't list what specific checks or outputs are produced.

2 / 3

Completeness

It answers 'what' (consistency and quality analysis across three artifacts) and partially implies 'when' ('after task generation'), but there is no explicit 'Use when...' clause with trigger guidance, which caps this at 2 per the rubric.

2 / 3

Trigger Term Quality

Includes some relevant terms like 'spec.md', 'plan.md', 'tasks.md', 'consistency', and 'quality analysis', but misses natural user phrases like 'review tasks', 'check plan', 'validate spec', or 'verify alignment'. The phrase 'non-destructive cross-artifact consistency' is more technical jargon than natural language.

2 / 3

Distinctiveness Conflict Risk

The description targets a very specific niche — cross-artifact consistency checking across exactly spec.md, plan.md, and tasks.md after task generation. This is unlikely to conflict with other skills due to its narrow, well-defined scope.

3 / 3

Total

9

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

9

/

11

Passed

Repository
mixpanel/mixpanel-headless
Reviewed

Table of Contents

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