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danilop

kiro-total-recall

by danilop

search_project_history

Find past decisions, implementation details, bugs, and architecture choices by searching workspace-specific conversation history. Supports keyword queries, date filters, and context around matches.

Instructions

Search conversation history for the CURRENT WORKSPACE only.

Use this to find workspace-specific context: past decisions, implementation details, bugs discussed, architecture choices in this codebase.

Args: query: Keywords or sentence describing what to find after: Filter to messages on/after this date (ISO 8601: "2025-01-15") before: Filter to messages before this date (ISO 8601) context_size: Messages to include before AND after each match (default: 3) threshold: Minimum similarity 0-1 (default: 0.2) max_results: Maximum results to return (default: 10) offset: Skip results for pagination (default: 0)

Returns: Search results with matched messages, scores, context, and pagination info

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
queryYes
beforeNo
offsetNo
thresholdNo
max_resultsNo
context_sizeNo
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the scope (current workspace) and parameter behavior but does not explicitly state read-only nature. The behavior is clearly a search operation without side effects.

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?

The description is well-structured: a concise intro sentence, a usage guidance paragraph, and a clear Args list. Every sentence adds value, with no fluff or repetition.

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?

Given no output schema, the description mentions return structure (messages, scores, context, pagination info). Parameter documentation is complete. However, it could be slightly more detailed about the return format, but it is sufficient for an agent.

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 the description compensates fully with an explicit Args section explaining each parameter's purpose, type, and default. This adds substantial meaning beyond the bare schema.

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 conversation history for the current workspace only. The verb 'search' and resource 'project history' are specific, and it distinguishes from siblings like search_global_history by emphasizing workspace scope.

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

Usage Guidelines4/5

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

It explicitly says to use for workspace-specific context and implies not for global searches. It names sibling tools but does not explicitly tell when to use alternatives. However, the scope restriction is clear.

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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