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emretheus
by emretheus

remind_search

Search past Claude Code conversations to find already-solved solutions to recurring problems, returning ranked hits with resume commands.

Instructions

Search past Claude Code sessions for solutions to recurring problems. Returns BM25-ranked hits with a snippet, a solvedHint, a messageUuid, and a ready-to-paste claude --resume <id> command.

When to use: at the start of a task to check for prior work on the same codebase; or when the user mentions an error, tool, or feature they may have already solved. One call is usually enough — only re-call with a different query if the first returned no useful hits.

Query tips: use specific concrete terms — exact error strings (ExpiredTokenException, LoginRefreshRequired), tool/lib names (BuildKit, Cognito, Tailwind), or real file paths (tailwind.config, shared_auth/jwt.py). Avoid generic words that flood the corpus (e.g. AWS, auth, docker on their own). Good: ExpiredTokenException SendSSHPublicKey. Bad: AWS auth issue.

Cost: ~1–2 KB per call at default (5 hits, 1000-char snippets). Use format: "compact" (400 chars) for cheap scans, format: "full" (2000 chars) when you need to read in place. After finding a relevant hit, call remind_message with its messageUuid to read the full content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFree-text search query.
projectNoOptional. Substring match against the session's cwd (e.g. 'my-app').
limitNo
sinceDaysNoOptional. Only include sessions updated within the last N days.
formatNoSnippet length: compact=400, detailed=1000, full=2000 chars.detailed
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the search algorithm (BM25), return fields (snippet, solvedHint, messageUuid, resume command), cost per call, and format options. Does not mention rate limits or token budgets, but for a search tool this is sufficient.

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?

Information is front-loaded with the core purpose, then usage guidelines, query tips, and cost details. Every sentence adds value; no redundancy or filler. Well-structured into clear sections.

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 the lack of output schema, the description thoroughly explains return values and actionable follow-up (call remind_message). It covers all aspects an agent needs: when to use, query formulation, format options, and cost awareness. Complete for a search tool.

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 80%, and the description adds significant value beyond schema: explains query tips (specific terms to use/avoid), defines enum values for format (compact=400 chars, etc.), and suggests project substring matching usage. The description compensates well for the remaining undocumented parameter aspects.

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 searches past Claude Code sessions for solutions, with a specific verb and resource. It effectively distinguishes itself from siblings like remind_message (for reading full content) and remind_resume (likely resuming sessions).

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?

Explicit guidance on when to use: at task start or when user mentions a problem. Advises one call is sufficient, and provides query tips with good/bad examples. Clearly tells the agent when not to re-call unnecessarily.

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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