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rdnpradipta

Muninn

by rdnpradipta

save_hyde

Store a hypothetical answer as a searchable HyDE bridge so retrieval misses become indexed hits.

Instructions

Persist a HyDE hypothetical document as a reusable type=hyde bridge.

Use after a search(query, hypothesis=...) fallback produced good grounding, so the same retrieval miss becomes an indexed hit next time (searchable via note_type="hyde" or "everything"). A hyde bridge is generated text, never a citable source. Idempotent per (doc_id, query) — re-saving updates in place.

Args: query: the user query this hypothesis answers (used for the bridge id). hypothesis: the hypothetical answer paragraph to store and embed. doc_id: optional document this bridge is about ("" = corpus-wide). title: optional label ("" = derived from the query).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
titleNo
doc_idNo
hypothesisYes
Behavior5/5

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

No annotations are provided, so the description carries full burden. It discloses idempotency per (doc_id, query), in-place updates, the non-citable nature, and searchability via note_type.

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?

The description is well-structured with a clear lead sentence and a bullet-like list for arguments. It is slightly long but every sentence adds value; could be slightly more terse.

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 no output schema and 0% schema coverage, the description fully explains inputs, idempotency, use case, and integration with other tools (searchable via note_type). It is complete.

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

Parameters5/5

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

Schema coverage is 0%, so description must explain parameters. It thoroughly describes each parameter: query (user query and bridge id), hypothesis (answer paragraph), doc_id (optional scope), title (optional label derived from query).

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 uses a specific verb ('Persist') and resource ('HyDE hypothetical document'), and distinguishes this tool from siblings by specifying it's for hypothetical documents and creates a 'type=hyde bridge' for search.

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?

The description explicitly states when to use: after a 'search(query, hypothesis=...) fallback produced good grounding', and what not to use for: 'never a citable source'. It also mentions idempotency and searchability via note_type.

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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