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

No annotations provided, so description carries full burden. It discloses multiple behavioral traits: reads messages (read operation), supports pagination via offset/limit, truncation via maxChars, and source filtering. It does not mention side effects or return format, but for a read-only tool these are acceptable. No contradiction with annotations.

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

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

Two sentences, front-loaded with purpose, no wasted words. Efficient and clear.

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

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

Given 5 parameters, no output schema, and no annotations, the description covers key usage (source of IDs, pagination) but lacks details on return format, error handling, or session not found behavior. Completeness is adequate but not exceptional.

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

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

Schema already has descriptions for 4 of 5 parameters (80% coverage). Description adds context about pagination but does not detail all parameters beyond schema. Baseline 3 is appropriate; description adds minimal extra meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Read the messages of a single conversation session by ID', specifying the verb ('Read'), resource ('messages of a single conversation session'), and source of IDs (list_sessions or search_history). It distinguishes from sibling tools: list_sessions returns sessions, search_history searches, get_session reads a specific session's messages.

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

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

Explicitly says to use after obtaining session ID from list_sessions or search_history, and mentions pagination for long sessions. Sibling tools are listed, providing context for when not to use this tool. Could be improved by explicitly stating when not to use, but adequate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden. It discloses the tool lists recent sessions, orders them newest first, and covers multiple sources. It does not mention rate limits or output format, but for a list tool the behavioral disclosure is adequate.

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

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

Two sentences, front-loaded with purpose, no wasted words. Every sentence provides value (purpose, usage example, link to get_session).

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

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

With 3 optional parameters and no output schema, the description covers the tool's purpose, usage context, and ordering. It lacks a hint about the return format (e.g., session IDs, timestamps), but the context is largely complete for an agent to decide to use it.

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

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

Schema description coverage is 67% (source and project described, limit missing description). The tool description does not add further semantic meaning beyond the schema; it relies on schema for limit constraints and source/project descriptions, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('list') and resource ('local Claude sessions'), specifies ordering ('newest first'), and distinguishes from siblings by mentioning its use for finding a session ID to pass to get_session.

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

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

The description explicitly states when to use it ('reviewing what you worked on today/this week' or 'find a session ID to pass to get_session'), providing clear context. It does not explicitly state when not to use it or directly compare to search_history, but the sibling tool names imply differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries full burden. It discloses the tool is read-only (search), returns snippets and session IDs, searches newest first, works on local storage, and supports sources (code, cowork). It doesn't mention regex or maxPerSession directly, but those are in the schema.

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

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

Three sentences with no wasted words. First sentence states the core function, second explains output and links to sibling tool, third gives examples and ordering. Front-loaded and efficient.

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

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

Given no output schema, the description adequately explains return values (snippets, session IDs) and ordering. It covers main behavioral aspects for a 9-parameter search tool, though it doesn't elaborate on all parameters (schema covers them).

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

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by explaining the search order, multiple sources, and the relationship to get_session, aiding the agent in understanding how parameters like source and ordering affect results.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs full-text search across local conversation history from two sources (Claude Code and Claude Cowork), returns message snippets with session IDs, and differentiates from sibling tool get_session by directing users to read full conversations there. It also provides concrete example queries.

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

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

The description gives explicit usage context ('good for questions like...'), states the ordering ('searches newest sessions first'), and references get_session as the tool for full conversations. However, it does not explicitly specify when not to use this tool or mention alternatives like list_sessions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.