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RAGDown

by cubicecho
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TypeScript
Local

Context for a prompt

ragdown_context
Read-only

Inject relevant Markdown context into user prompts as a hook-ready block, filtering low-similarity matches and skipping sections already sent in a session.

Instructions

For hooks that run before a turn: the documents related to a user prompt, as a ready-to-inject block, or empty text when nothing is similar enough. Unlike ragdown_recall it filters by min_score, skips short prompts and slash commands, and never returns a section twice for the same session_id. reset: true first forgets what that session was given; call it with an empty prompt after the client compacts or clears its context. format: 'claude-code' wraps the block as the JSON a Claude Code UserPromptSubmit hook adds to the prompt.

Input Schema

NameRequiredDescriptionDefault
resetNoForget the sections already returned for session_id before answering, because the client no longer has them
top_kNoDefault RAGDOWN_HOOK_TOP_K
formatNo'text' is the block itself. 'claude-code' is the block as a Claude Code hook's additionalContext, for an mcp_tool hook on UserPromptSubmit, which does not pass plain text on to the modeltext
promptYesThe user's prompt, verbatim
max_charsNoMost characters in the block. Default RAGDOWN_HOOK_MAX_CHARS
min_ratioNoLowest share of the best hit's similarity a hit may have and still be included; 0 keeps every hit above min_score. Default RAGDOWN_HOOK_MIN_RATIO
min_scoreNoLowest cosine similarity to include. Default RAGDOWN_HOOK_MIN_SCORE
session_idNoStable id of the conversation; sections already returned for it are skipped

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv5.16.0
    • addedInput schema / properties / format
      Added value: +{
+  "default": "text",
+  "description": "'text' is the block itself. 'claude-code' is the block as a Claude Code hook's additionalContext, for an mcp_tool hook on UserPromptSubmit, which does not pass plain text on to the model",
+  "enum": [
+    "text",
+    "claude-code"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / reset
      Added value: +{
+  "default": false,
+  "description": "Forget the sections already returned for session_id before answering, because the client no longer has them",
+  "type": "boolean"
+}
  2. Addedv4.0.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint, not openWorld), but the description discloses non-obvious stateful behavior they cannot: per-session dedup ('never returns a section twice for the same session_id'), the reset-forgets-sections semantics, skip rules for short prompts/slash commands, and the empty-string return condition. It stops short of error/failure behavior or the exact shape of the returned block, so it is strong but not exhaustive.

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?

Three dense sentences with no filler, and the primary purpose is front-loaded before the sibling comparison. The reset/format guidance reads as compressed notes rather than prose, which slightly hurts readability but not information density.

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?

With no output schema, the description carries the return-value burden and does so (block vs. empty text). Given 8 parameters fully documented in the schema, the annotations covering safety, and the description covering purpose, routing, statefulness, and return semantics, an agent has everything needed to call it correctly.

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 the baseline is 3; the description nonetheless adds real meaning the schema lacks for reset (what is forgotten, and the empty-prompt idiom after compaction) and format (why 'claude-code' exists — the hook does not pass plain text through). The remaining numeric knobs are left entirely to the 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?

Names a specific verb and resource (retrieve documents related to a prompt) plus the exact artifact returned (a ready-to-inject <ragdown-context> block or empty text) and the execution context (pre-turn hooks). It explicitly distinguishes itself from the sibling ragdown_recall, so an agent can route without opening either schema.

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 states when to use it ('for hooks that run before a turn') and names the alternative plus the selecting conditions ('Unlike ragdown_recall it filters by min_score, skips short prompts and slash commands'). It also gives concrete invocation guidance for reset ('call it with an empty prompt after the client compacts or clears its context') and when to pick the claude-code format.

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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