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cachly-dev

cachly — AI Cognitive Brain

autopilot

Writes a configuration file that makes AI editors automatically call memory hooks at session open, after every fix, and before close, ensuring persistent context.

Instructions

Generate a CLAUDE.md / copilot-instructions.md that makes any AI self-managing forever. Writes a configuration file to disk — will overwrite an existing file at the target path. No auth required beyond a valid instance_id. The generated file instructs Claude, Cursor, Copilot, Windsurf, or Gemini to automatically call session_start at window open, learn_from_attempts after every fix, and session_end before closing — without being asked. Returns the generated file content as a string and the path where it was written. Use style="minimal" for just the three hooks; style="full" for the complete ruleset with examples. One command. Every AI. Always on. Use setup_ai_memory instead if you want an interactive one-shot setup that also creates an instance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idYesUUID of the cache instance
editorNoTarget editor (default: claude)
project_nameNoYour project name (used in generated instructions)
styleNominimal = just the hooks, full = full ruleset with examples (default: full)
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses key behaviors: overwrites existing files, no auth beyond instance_id, and details the generated file's hooks. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is somewhat long but each sentence adds value. Front-loaded with purpose. Could be slightly trimmed but remains clear and informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, no output schema, description covers return value (file content and path), safety (overwrite), auth, and usage alternatives. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline 3. Description adds value by explaining style enum values ('minimal' vs 'full') and editor default, going beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a CLAUDE.md / copilot-instructions.md for AI self-management, distinguishes from sibling tool setup_ai_memory by specifying an alternative use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly mentions file overwrite behavior, auth requirements (valid instance_id), and provides an alternative tool for interactive setup. Guides agent on when to use autopilot vs. setup_ai_memory.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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