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coding-agent

Authoring playbook for building agents that write, edit, review, or refactor code. Use this when the user asks for an agent that writes scripts, generates code, reviews pull requests, refactors a codebase, fixes bugs, implements features, writes tests, or works with programming languages such as Python, TypeScript, JavaScript, Go, Rust, SQL, or shell.

72

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%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 strong, dense playbook: it delivers a complete, adaptable system prompt template with exact rules, explicit completion criteria, and a worked example, without wasting tokens on concepts Claude already knows. The main improvement opportunities are removing the duplication between the inline and closing worked examples and making the builder-facing sequence explicit as numbered steps.

DimensionReasoningScore

Conciseness

The body never explains concepts Claude already knows and stays prescriptive throughout ('Never invent APIs, function signatures, package names...', 'Do NOT attach generic web-browsing tools...'). It is not a 5 because the closing 'Worked example (full)' partially duplicates the example embedded in the system prompt template, and the required verbatim line is stated twice (emphasis section plus template), which could be trimmed.

4 / 5

Actionability

It provides a complete fill-in-the-blank system prompt template, an exact verbatim line to enforce, concrete name/description patterns ('Python Data Scripter', 'Bug Fix Engineer'), a tool-priority list, and a full worked example that produces the final artifact (name, description, tools, prompt excerpt). The guidance is directly executable for the agent-building task.

5 / 5

Workflow Clarity

Mode-selection decision logic is explicit ('use this only when the agent has file/repository access'), and the 'Completion criteria — you are NOT done until' checklist provides explicit validation checkpoints including an escape hatch ('If a check cannot be run, state the exact reason'). It is not a 5 because the builder-facing procedure (pick identity, choose mode, fill template, attach tools, check anti-patterns) is implied by section order rather than presented as an explicit numbered sequence with checkpoints.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are all absent), so there are no nested or buried references, and the single file has clear, scannable section headers. It is not a 5 because at ~135 lines everything is inlined — including two worked examples and the full template — where the full worked example could live in a reference file; this leaves minor organization gaps rather than a well-split overview.

4 / 5

Total

17

/

20

Passed

Description

96%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.

An excellent description: it states a concrete what, an explicit and richly populated when-clause with natural trigger terms, and stays in third person without padding. Its only weakness is that the individual coding keywords are so common that keyword-level matching could pull it in for plain coding requests rather than agent-authoring requests.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'building agents that write, edit, review, or refactor code', 'writes scripts, generates code, reviews pull requests, refactors a codebase, fixes bugs, implements features, writes tests' — giving comprehensive coverage of the domain. It exceeds anchor 4 because there are no minor gaps in the action list for the coding-agent authoring niche.

5 / 5

Completeness

It explicitly answers what ('Authoring playbook for building agents that write, edit, review, or refactor code') and when ('Use this when the user asks for an agent that...') with concrete trigger phrases. Both halves are explicit and concrete, matching the top anchor exactly.

5 / 5

Trigger Term Quality

Natural user phrasings are comprehensively covered ('fixes bugs', 'writes tests', 'reviews pull requests', 'refactors a codebase') along with specific language names users would say (Python, TypeScript, JavaScript, Go, Rust, SQL, shell). Only near-synonyms like 'programming' or 'developer' are absent, so it sits at the top anchor rather than 4.

5 / 5

Distinctiveness Conflict Risk

The 'when the user asks for an agent that...' framing establishes a clear niche distinct from plain coding skills, but the raw keywords (code, Python, bug, tests, PR) are extremely common and could overlap with general coding skills or sibling agent-authoring playbooks if matched on terms alone. This is 'mostly distinct; minor overlap risk', not the minimal-conflict top anchor.

4 / 5

Total

19

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mastra-ai/mastra
Reviewed

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