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

Annotations already mark this as idempotent and non-destructive, and the description adds meaningful behavioral invariants: the capability profile and filesystem root stay unchanged, ChatGPT remains the sole main model, worktree behavior depends on session type, and a DeepSeek subagent cannot take over the main loop. These details go beyond what annotations or schema convey.

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?

The description is compact and front-loaded with the core purpose, then adds behavior details about session types and the DeepSeek subagent. Each sentence contributes useful information, though the session-type sentences could be seen as elaborating what the first sentence already implies.

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 the 100% schema coverage, the presence of an output schema, and annotations covering idempotency and safety, the description supplies enough behavioral context for an agent to invoke the tool correctly. The only notable gap is the lack of explicit routing guidance against sibling continuation-related tools.

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 five parameters thoroughly. The description adds high-level session context but does not add parameter-specific semantics beyond what is already present in the input schema.

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?

Clearly states the action: continue the same durable native session while preserving its capability profile, filesystem root, and main model. This distinguishes it from starting a new session, though it does not explicitly differentiate it from siblings like native_session_recover or native_session_reply_and_wait.

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 implies this tool is for resuming an existing durable session rather than starting a new one, but it never explicitly names alternatives or states when to prefer this over native_session_recover or native_session_reply_and_wait. The guidance is contextual but not directive.

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?

Annotations already convey idempotency and non-destructiveness; the description adds meaningful context by stating that ChatGPT remains the sole main model, that DeepSeek access is limited by the original subagent policy, and that a write session requires verification of its directory or worktree binding. This goes beyond the annotations and helps an agent understand important constraints.

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?

The description is reasonably concise and front-loaded with the primary action. The second and third sentences add important behavioral constraints, though the third sentence is dense and slightly harder to parse. Overall, no sentence feels purely redundant.

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?

The description covers the core purpose and key constraints, and the output schema likely handles return-value expectations. However, it lacks explicit usage guidance, does not differentiate from sibling tools, and does not state what happens when verification fails or the lease cannot be rotated. These are meaningful gaps for a recovery operation.

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 four parameters. The description does not add parameter-level meaning beyond the schema, such as the relationship between wait_seconds and lease rotation or the origin of the recovery token. Per baseline for high schema coverage, a 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 opens with a specific verb and resource: 'Reconnect ChatGPT to a durable native Claude Code session and rotate its lease.' This clearly conveys the core action. It does not explicitly name or contrast sibling tools, so it stops short of fully distinguishing itself from tools like native_session_continue.

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 explicit guidance on when to use this tool versus siblings such as native_session_continue, native_session_status, or native_session_reply_and_wait. The word 'Reconnect' loosely implies a recovery scenario, but no conditions, alternatives, or exclusions are stated.

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?

Annotations mark the call as destructive and idempotent; the description adds substantial behavioral context by enumerating per-profile permissions (network-blocked read-only RunCommand, direct_write vs worktree_write roots) and the deepseek_explicit subagent exception. It does not explicitly describe the waiting/blocking behavior implied by the name, but the policy detail goes well beyond the 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?

The description is roughly 130 words and opens with the core action in the first sentence. Each following sentence covers a distinct policy area without significant redundancy, making it dense but not bloated.

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 tool this complex, the description covers the essential constraints: exact turn targeting, sole main-model ownership, per-profile permissions, and subagent limitations. The wait behavior is only hinted at by the tool name, and the description does not state what happens after submission, though an output schema exists to fill return-value gaps.

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 the baseline is 3. The description adds a useful summary of which tool_calls are permitted and restates the sole-call rule for DeepSeek start, but it does not individually explain native_session_id, lease_id, turn_id, or reply_id beyond what the schema already documents.

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 first sentence states a specific action: 'Submit ChatGPT's response for one exact pending native turn.' It identifies the verb, the resource, and the exactness constraint, which clearly separates it from the session lifecycle siblings. The 'ChatGPT is always the sole main model' line further clarifies its role in the 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 implies the required condition—'one exact pending native turn'—and gives operational rules for tool_calls, such as 'DeepSeek start must be the only call.' However, it never explicitly contrasts this tool with siblings like native_session_continue or states when not to use it.

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 annotations already marking idempotentHint=true and destructiveHint=false, the description adds rich behavioral context: isolated session, subagent_policy default, restricted tool capabilities (network-blocked, filesystem-read-only RunCommand), protected credential/state paths, working_directory as the only write root for write profiles, and read_only never writes. This gives the agent a clear model of side effects and boundaries.

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?

The description is front-loaded with the core purpose in the first sentence and every subsequent sentence carries meaningful constraint information. It is a dense paragraph rather than structured bullets, and a couple of details (subagent_policy defaults to none) duplicate the schema, but it is appropriately concise for a tool with this many behavior-affecting choices.

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 the rich input schema, output schema, and annotations, the description covers all invocation-critical decisions: profile selection, subagent policy, working directory semantics, tool restrictions, and write behavior. Nothing needed to call the tool correctly is missing.

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 the baseline is 3. The description adds useful decision semantics on top: capability_profile selection guidance (read_only never writes, direct_write works for Git/non-Git, worktree_write only for clean Git), the write-root constraint, and the deepseek_explicit-worktree coupling. Some of this duplicates schema text, but 'only write root' and 'read_only never writes' add meaning beyond the param descriptions.

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 opening sentence states the exact action: start an isolated native Claude Code session with the current ChatGPT conversation as sole main model. This is a specific verb + resource and distinguishes native_session_start from the continue/recover/reply_and_wait/status/stop siblings by the 'start' action.

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 clearly tells when to choose direct_write (explicit user request to modify actual files, Git or non-Git) and worktree_write (isolated copy of a clean Git repo), and ties deepseek_explicit to worktree_write. It does not explicitly name sibling tools or state when to use start over continue/recover, so it falls short of full alternative routing.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior, and the description adds meaningful context beyond those flags: it explicitly states no session advancement and no model invocation, and clarifies that only safe summaries of enabled DeepSeek subagents and the managed-worktree location are returned. This substantially helps an agent predict 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.

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

The description is two sentences with no filler. The most decision-relevant facts—reading state, not advancing, not invoking a model—are front-loaded, and the second sentence adds precise return-value context without unnecessary length.

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 the output schema, 100% parameter coverage, and annotations that already define safety characteristics, the description supplies the remaining context an agent needs: the tool is side-effect-free, returns safe summaries when present, and preserves ChatGPT as the sole main model. Nothing essential is missing for correct invocation.

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 input schema already documents all parameter meanings. The description does not add significant parameter-level detail beyond what the schema provides, so the baseline score of 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 ('Read') with a clear resource ('native-session state') and adds a key distinguisher: the operation does not advance the session or invoke a model. It also names exactly what information is returned, making the tool's purpose unmistakable relative to its siblings.

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 phrase 'without advancing it or invoking a model' clearly establishes this as a non-mutating status-check tool, implying use when state is needed without side effects. It does not explicitly name alternatives like native_session_continue, so there is some room for inference, but the intended context is clear.

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?

Annotations already declare destructiveHint and idempotentHint, but the description adds valuable context: durable state and worktree are preserved for inspection, the main ChatGPT model is untouched, and Session-owned DeepSeek subagents must be safely stopped. 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?

The description is concise and front-loaded with the primary action. The second sentence about ChatGPT remaining the sole main model is slightly tangential but adds context; overall every sentence is short and purposeful.

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?

The description covers the core purpose, a prerequisite, and the side-effect guarantee of preservation. With a full output schema and complete parameter schema, nothing critical is missing; retry semantics are already implied by the idempotentHint annotation.

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 baseline of 3 applies. The description itself does not add meaning beyond the schema, but each parameter is already fully documented in the schema with origin, format, and purpose.

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 states a specific verb and resource: it stops the isolated native-session process and preserves durable state and managed worktree for inspection. It also clarifies the tool's relationship to the main model, making the action unambiguous. This clearly distinguishes it from the sibling start/continue/recover/status tools.

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 implies when the tool should be used by stating that active subagents must be safely stopped and durably observed 'before the Session can finalize.' However, it does not explicitly name alternative tools or give explicit when-not-to-use guidance, so it stops short of a 5.

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