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Search Raw Archive

search_raw
Read-onlyIdempotent

Search the raw archive of every user/assistant turn to recall literal phrases from past chats when curated search returns no match. Returns untreated conversation content, so expect noise.

Instructions

Search the raw archive (every user/assistant turn captured by the Stop hook). Use this when search returns no curated match or you need to recall a literal phrase from past chats. Returns the untreated conversation content — expect noise. The raw archive is what guarantees 'what was said remains searchable' even when summarize/promote skip a turn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleNoRole filter: 'user' or 'assistant' (default: both)
limitNoMax results to return (default 20)
queryYesRaw FTS query across every user/assistant turn captured by the raw archive. Unlike `search`, this bypasses all curation and returns literal chat content. Use when `search` comes back empty or you need to recall an exact phrase from past conversations.
sinceNoOnly rows at or after this time (Unix epoch, ISO8601 datetime, or YYYY-MM-DD)
untilNoOnly rows at or before this time (Unix epoch, ISO8601 datetime, or YYYY-MM-DD; a date includes that full UTC day)
branchNoGit branch filter. Returns raw rows for this branch plus older rows without branch metadata.
offsetNoResult offset for pagination
projectNoProject name filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYes
roleNo
countYes
limitYes
queryYes
branchNo
offsetYes
projectNo
resultsYes
has_moreYes
next_offsetNo
since_epochNo
source_typeYes
until_epochNo
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. It adds valuable context: results are 'untreated conversation content — expect noise' and explains the raw archive's role in guaranteeing searchability even when summarize/promote skip a turn. This goes beyond the structured annotations without contradicting them.

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

Conciseness5/5

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

Three sentences, each earning its place: purpose, when-to-use, and behavioral expectations. No fluff, front-loaded with the core action, and well-structured for quick comprehension.

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

Completeness4/5

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

With an output schema present, return values are covered. The description explains the tool's niche within the broader toolset (raw vs curated), the data scope ('every user/assistant turn captured by the Stop hook'), and the noise caveat. This is sufficient for a search tool, though it could briefly mention the supported filters (time, branch, project) to aid in selecting parameters, but the schema already covers those.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are fully documented in the schema. The description adds high-level context (raw FTS, bypasses curation) but does not elaborate on individual parameters beyond what the schema already provides. At full schema coverage, a baseline of 3 is appropriate.

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 ('Search') and clearly identifies the resource ('raw archive of every user/assistant turn captured by the Stop hook'). It explicitly contrasts with the sibling tool `search`, noting when to use each, which fully distinguishes it from alternatives.

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?

It explicitly states when to use this tool: 'when `search` returns no curated match or you need to recall a literal phrase from past chats.' It also warns that results are untreated and noisy, setting clear expectations and contrasting with the curated `search` alternative.

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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