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tools

Give your agents capabilities through tools (function calling). Helps you identify what your agent needs to do, create tool definitions, and attach them to config variations.

49

Quality

52%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/agentcontrol/tools/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

55%

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

The skill excels at actionability with concrete, executable code and a clear 4-step workflow with verification. However, it is severely bloated — the per-provider conversion snippets, agent loop skeleton, and provider comparison table make this far too long for a SKILL.md overview. Most of this reference material should be split into separate files, with the main skill providing a concise overview and clear pointers.

Suggestions

Move the per-provider schema conversion table and Python snippets into a separate reference file (e.g., PROVIDER-SCHEMAS.md) and link to it from the main skill.

Move the agent loop section (skeleton code and per-provider stop-reason details) into a separate reference file (e.g., AGENT-LOOP.md) since it's supplementary to the core tool creation workflow.

Remove explanatory text that Claude already knows, such as 'An agent that uses tools runs a short loop: call the provider, dispatch any tool calls, loop again, stop when the provider returns a final answer.'

Keep the main SKILL.md focused on the 4-step workflow (Identify → Create → Attach → Verify) with minimal inline examples, using progressive disclosure to reference detailed provider-specific content.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~200+ lines. The per-provider conversion table, full Python conversion snippets for 4 providers, and the entire agent loop skeleton are extensive reference material that could be in separate files. The agent loop section explains concepts Claude already knows (what a tool loop is, how stop reasons work). Much of this content doesn't earn its token cost in the main SKILL.md.

1 / 3

Actionability

The skill provides fully executable code examples throughout — JSON schema examples, complete Python conversion snippets for multiple providers, a full agent loop skeleton with Anthropic, and concrete MCP tool call sequences. The workflow steps specify exact tool names and parameters.

3 / 3

Workflow Clarity

The 4-step workflow (Identify → Create → Attach → Verify) is clearly sequenced with explicit verification in Step 4. The skill includes important validation checkpoints (confirm tool exists, confirm attachment), a feedback loop for the listing-first path, and explicit warnings about destructive behavior (clobbering UI edits). Edge cases are documented with specific actions.

3 / 3

Progressive Disclosure

This is a monolithic wall of content. The per-provider conversion table, all Python conversion snippets, the full agent loop skeleton, and the provider-specific tracking references should be in separate reference files. The skill references external files (e.g., openai-tracking.md, anthropic-tracking.md) but still inlines massive amounts of content that belongs in those references. No bundle files are provided to offload this content.

1 / 3

Total

8

/

12

Passed

Description

50%

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 communicates the general domain (agent tool/function calling setup) and lists some actions, but lacks an explicit 'Use when...' clause, uses second person ('Helps you'), and could be more concrete about specific capabilities. It would benefit from sharper trigger terms and clearer guidance on when Claude should select this skill.

Suggestions

Add an explicit 'Use when...' clause with trigger terms like 'tool use', 'function calling', 'tool schema', 'agent tools', 'define tools for an agent'.

Replace second person ('Helps you identify') with third person ('Identifies what an agent needs, creates tool definitions, attaches them to config variations') to match expected voice.

Include more specific natural keywords users might say, such as 'tool schema', 'JSON schema', 'API tools', 'tool parameters', or 'agent configuration'.

DimensionReasoningScore

Specificity

Names the domain (agent tools/function calling) and some actions ('identify what your agent needs to do, create tool definitions, attach them to config variations'), but the actions are somewhat vague—'identify what your agent needs to do' is abstract rather than concrete.

2 / 3

Completeness

The 'what' is partially addressed (create tool definitions, attach to config variations), but there is no explicit 'Use when...' clause or equivalent trigger guidance telling Claude when to select this skill. Per rubric guidelines, missing 'Use when' caps completeness at 2.

2 / 3

Trigger Term Quality

Includes relevant keywords like 'tools', 'function calling', 'tool definitions', and 'config variations', but misses common user phrasings like 'API tools', 'tool use', 'tool schema', 'JSON schema', or 'agent configuration'. Coverage of natural variations is incomplete.

2 / 3

Distinctiveness Conflict Risk

The mention of 'tools (function calling)' and 'config variations' provides some specificity, but 'agents' and 'capabilities' are broad terms that could overlap with other agent-building or configuration skills.

2 / 3

Total

8

/

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
launchdarkly/ai-tooling
Reviewed

Table of Contents

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