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update-entry-points

Generate talkpipe.sources and talkpipe.segments entry points from @register_source/@register_segment decorators and update pyproject.toml. Use when adding new sources or segments to TalkPipe, or when entry points are out of sync with the codebase.

96

1.01x
Quality

93%

Does it follow best practices?

Impact

100%

1.01x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

87%

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, concise skill that provides clear, executable guidance for updating entry points. Its main weakness is the lack of an explicit validation step in the workflow—recommending --dry-run before the actual run would make the workflow more robust for a file-modifying operation. Otherwise, the content is efficient, actionable, and well-structured.

Suggestions

Integrate --dry-run into the recommended workflow as an explicit first step (e.g., 'Run with --dry-run first to verify changes, then run without to apply'), which would strengthen the validation checkpoint for this file-modifying operation.

DimensionReasoningScore

Conciseness

The content is lean and efficient. Every section serves a purpose—no explanation of what entry points are, no unnecessary background on decorators or TOML. Assumes Claude understands the domain and gets straight to actionable content.

3 / 3

Actionability

Provides exact executable commands to run the script, a clear options table with flags, and a concrete manual fallback with specific commands and file paths. Everything is copy-paste ready.

3 / 3

Workflow Clarity

The workflow steps are listed clearly, but there's no validation checkpoint after running the script. A --dry-run option exists but isn't integrated into a recommended workflow (e.g., 'run with --dry-run first, verify diff, then run without'). For an operation that modifies pyproject.toml, a verify-then-apply pattern would be appropriate.

2 / 3

Progressive Disclosure

For a simple, single-purpose skill under 50 lines, the content is well-organized with clear sections (When to Use, Workflow, Options, Manual Fallback). The script reference points to a bundled file at a clear path. No need for additional file references given the scope.

3 / 3

Total

11

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is an excellent skill description that clearly defines specific actions (generating entry points, updating pyproject.toml), includes domain-specific trigger terms that users would naturally use, and explicitly states both what the skill does and when to use it. The description is concise, uses third-person voice, and occupies a very distinct niche that minimizes conflict risk with other skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: generating talkpipe.sources and talkpipe.segments entry points from decorators, and updating pyproject.toml. These are precise, actionable capabilities.

3 / 3

Completeness

Clearly answers both 'what' (generate entry points from decorators and update pyproject.toml) and 'when' (when adding new sources/segments to TalkPipe, or when entry points are out of sync with the codebase) with an explicit 'Use when' clause.

3 / 3

Trigger Term Quality

Includes natural keywords a developer would use: 'entry points', 'sources', 'segments', 'TalkPipe', '@register_source', '@register_segment', 'pyproject.toml', 'out of sync'. These are terms a user working in this domain would naturally mention.

3 / 3

Distinctiveness Conflict Risk

Highly specific to the TalkPipe project's entry point generation workflow with distinct triggers like '@register_source', '@register_segment', 'talkpipe.sources', 'talkpipe.segments', and 'pyproject.toml'. Very unlikely to conflict with other skills.

3 / 3

Total

12

/

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
sandialabs/talkpipe
Reviewed

Table of Contents

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