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ai agent skill discovery matching
Rigorous, evidence-based matching of AI agent skills to tasks based on intent, capabilities, and hard constraints.
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ai agent skill discovery matching
Example session with this skill installed
Evaluate 'sql-optimizer-skill' against a task to optimize Postgres queries in a Node.js 20 environment. Ensure it supports JSONB indexing and requires no external API access for security.
- Read your context and instructions
- Compiled the ai agent discovery
I have analyzed the sql-optimizer-skill against your specific technical requirements for the Postgres optimization task.
Skill Match
Task
Optimize PostgreSQL queries in a Node.js 20 environment with JSONB support and zero external API access.
Requirements
- PostgreSQL Query Optimization: Required
- Node.js 20 Runtime Compatibility: Required
- JSONB Indexing Support: Required
- Zero External API Access: Hard Constraint (Security)
Candidate Analysis
sql-optimizer-skill
- Match: Partial Match
- Capability Fit: Directly supports SQL query plan analysis and indexing strategies for standard Postgres types.
- Constraint Fit: Operates locally via standard library calls; meets the zero external API access requirement.
- Gaps: Metadata does not explicitly confirm support for JSONB-specific indexing (e.g., GIN/GiST).
Conflicts: Declared compatibility is for Node.js 16+; while likely compatible with 20, it is not explicitly verified for the v20 runtime features.
- Evidence: Documentation confirms local processing and general Postgres support but is silent on JSONB.
| Requirement | Candidate Capability | Evidence | Status |
|---|---|---|---|
| Postgres Optimization | SQL Plan Analysis | Doc Section 2.1 | Match |
| Node.js 20 | Node.js 16+ Support | Package Metadata | Partial |
| JSONB Indexing | General Indexing | Unknown | Unknown |
| No API Access | Local Execution | Architecture Diagram | Match |
Match Rationale
The skill is a strong candidate for general SQL optimization and satisfies the critical security constraint of local execution. However, it is classified as a Partial Match because JSONB support—a specific requirement for your task—cannot be verified from the current metadata.
Limitations
Information regarding GIN index support for JSONB is
UNKNOWN. Compatibility with Node.js 20 is
INFERRED from the 16+ version requirement.
Next Action
- Inspect the skill's
indexing.jsfile to verify GIN index logic. - Run a local test in a Node.js 20 container to confirm runtime stability.
Next steps
- Check the source code for JSONB-specific keywords.
- Confirm if specific Node.js 20 globals are required by the skill logic.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Keyword matching for agent skills is unreliable. Developers often end up with tools that fail due to hidden dependency mismatches, runtime conflicts, or missing capabilities that were only discovered at execution time.
What it does
- Decomposes user requests into explicit, weighted capability requirements and hard constraints.
- Builds a structured requirement model including objective, inputs, outputs, and environment needs.
- Performs evidence-based mapping to identify Direct, Partial, and Indirect matches between tasks and skills.
- Detects capability gaps and runtime conflicts before you attempt to deploy the skill.
- Produces a match rationale that distinguishes between verified facts and inferences.
Why this beats prompting it yourself
Generic prompts rely on superficial similarity, often leading to hallucinated capabilities or ignored constraints. This skill enforces a strict evidence hierarchy and logic gate system to ensure that a match is technically viable, not just semantically related.
Use cases
- Audit a repository of custom agent skills to find the best fit for a complex orchestration pipeline.
- Validate if a specific third-party tool meets all security and runtime constraints of your environment.
- Identify specific capability gaps in your agent library that require new skill development.
- Compare multiple candidate skills against a single task objective using a standardized evidence table.
Known limitations
Cannot verify skill availability or runtime status for sources not accessible to the current environment. Discovery depends entirely on provided or accessible metadata.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
Free skills download straight away. Paid skills unlock right after purchase.
- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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