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pi-agent

Build with and use Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).

80

Quality

100%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

A well-structured overview skill: a tight decision table routes to verified one-level-deep references, with concrete commands and named APIs throughout. It respects the token budget and provides clear, actionable guidance without explaining concepts Claude already knows.

DimensionReasoningScore

Conciseness

Lean overview that assumes Claude's competence — a decision table, terse defaults, and runnable commands with no padding or explanation of basic concepts; every section earns its tokens.

3 / 3

Actionability

Provides concrete, executable commands (`npm install -g --ignore-scripts ...`, `pi --mode rpc --no-session`, `pi -p ...`) and named entry points (`createAgentSession()`, `createAgentSessionRuntime()`) that are copy-paste ready and complete.

3 / 3

Workflow Clarity

The 'First Decision' table gives an unambiguous selection sequence for every intent, and the Build-On-Pi/Safety Defaults sections act as explicit checkpoints before acting; for this navigation-style skill the single routing action is clear and validated against the reference list.

3 / 3

Progressive Disclosure

Body is a concise overview routing to ~30 one-level-deep references, all verified to exist in ./references/ (e.g. quickstart.md, sdk.md, rpc.md, pi-subagents.md); navigation is clearly signaled and content is appropriately split.

3 / 3

Total

12

/

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.

A strong, specific description with an explicit 'Use for' trigger clause and a broad, concrete capability list tied to named Pi ecosystem packages. It avoids vagueness and verbosity while staying in third person.

DimensionReasoningScore

Specificity

Lists many concrete actions (installing, configuring providers/models/settings, creating skills/extensions/packages/themes/templates, embedding via SDK, integrating over RPC/JSON streams, parsing sessions, developing custom providers/TUI components) — a comprehensive enumeration.

3 / 3

Completeness

Answers both 'what' (the enumerated capabilities) and 'when' via the explicit 'Use for ...' trigger clause, satisfying the explicit-trigger requirement.

3 / 3

Trigger Term Quality

Uses natural, user-sayable terms repeatedly — 'install', 'configure', 'providers/models/settings', 'embed', 'MCP servers', 'web search', 'video understanding' — with good coverage of common phrasings.

3 / 3

Distinctiveness Conflict Risk

Targets the single niche of the Pi harness and its specific named ecosystem packages, with distinct triggers unlikely to fire for unrelated 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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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