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

No annotations are provided, so the description carries the full behavioral burden for what is clearly a destructive operation. It never states that clearing is irreversible, whether an in-progress thinking session is affected, or whether confirmation/permissions are required — only the verb 'Clear' implies data loss.

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?

A single front-loaded sentence with no filler; the scope qualifier comes at the end but the core action leads. It is efficient, though it duplicates the title almost verbatim, so brevity comes at the cost of added information.

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?

For a destructive tool with no annotations, no output schema, and zero required parameters, the description is too thin. It omits irreversibility, default behavior when neither parameter is supplied, and any return/confirmation semantics an agent needs to call it safely.

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 100%, so the schema already documents 'session_id' and 'all_sessions'; baseline is 3. The description's 'one session or all sessions' loosely mirrors the two parameters but adds no format, default, or interaction details (e.g., behavior when both are omitted).

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?

Tautological: description restates name/title.

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?

There is no when-to-use or when-not-to-use guidance, no mention of prerequisites, and no pointer to the sibling get_thinking_history or sequentialthinking_tools. The phrase 'one session or all sessions' hints at the parameter choice but does not tell the agent which situation calls for which scope.

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 disclosure burden. It implies a read operation ('Return', 'inspect') but says nothing about ordering, truncation, default limits, or what a returned thought record looks like — for a history-retrieval tool with zero annotation coverage this is a meaningful gap.

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 short front-loaded sentences with no padding. The first sentence duplicates the title verbatim, which is mildly redundant rather than wasteful, so it stays efficient overall.

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?

For a simple three-parameter read tool whose schema is fully documented, the description is adequate but thin. With no output schema, it never describes the shape or content of returned thought records, leaving the agent to discover the return format empirically.

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 100%, documenting limit, branch_id, and session_id, so the baseline is 3. The description adds no meaning beyond the schema — it does not explain how branch_id interacts with session_id or what the limit default means in practice.

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?

Tautological: description restates name/title.

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?

'Use this to inspect or resume prior reasoning' gives implied usage context, but there is no explicit when-not guidance and no mention of the alternative clear_thinking_history or sequentialthinking_tools. The agent must infer which tool to pick.

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, the description carries the full behavioral burden. It does disclose one genuinely non-obvious trait: recommendations are validated, not generated, by this server. However, it omits persistence behavior, whether steps accumulate in a session, and what the recorded step does for subsequent calls.

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?

Compact and front-loaded: the core action leads, and the optional-input/validation caveat follows in one clause. No filler sentences, though the text largely mirrors the title.

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?

For a 13-parameter tool with no annotations and no output schema, the description covers purpose and one behavioral trait but says nothing about session persistence, iterative invocation, or return behavior. The rich schema compensates for the parameter gaps, keeping this at a minimum-viable level.

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 100%, so the schema already documents all 13 parameters, making a 3 the baseline. The description adds only a reinforcing note that recommendations are validated against available_tools rather than invented, which the schema already implies.

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?

Tautological: description restates name/title.

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?

There is no statement of when to call this versus the history siblings, no note that it is meant to be invoked repeatedly to build a chain, and no prerequisites. The only usage-adjacent content is that available_tools and recommended_tools are optional, which is parameter guidance rather than when-to-use guidance.

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