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

With no annotations, the description carries the full behavioral burden. It discloses the action (downloads to output directory) and the return format (local paths and manifest with URLs/licenses). It does not mention file overwriting, network requirements, or session validity, but these are minor gaps for a download tool.

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 that are tightly written: the first states the core action, the second states the return value. No filler, and the most important information is front-loaded.

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 essential function but omits the purpose of session_id and its relation to the broader search workflow. Without annotations or an output schema, an agent may not know if session_id must come from a prior start/iterate call or whether the output directory is session-scoped. This is incomplete for a multi-step tool.

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?

The description explains 'ids' with an example and meaning (round-qualified ids), but 'session_id' is not explained at all. Since schema description coverage is 0%, the description should have delineated both parameters; it partially compensates but leaves a critical gap on how session_id is used.

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 (download), resource (full-resolution images), and target (list of ids) with an example. It clearly distinguishes from siblings (start/iterate/status) which are about session management, not downloading.

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 usage by mentioning 'round-qualified ids' and downloading, but it never explicitly says when to use this tool versus siblings or that it should follow a prior step. The workflow relationship to image_search_start/iterate/status is left to inference, with no exclusions or explicit conditions.

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 burden. It discloses dedup against previously shown images and that the LLM interprets feedback into keyword changes via refine_search. However, it doesn't mention side effects like session mutation, reversibility, or any potential rate limits. It covers some key behaviors but not all.

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 with zero waste. The primary usage is front-loaded, and the key behaviors (dedup, LLM interpretation) are clearly stated. Very 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?

For a tool with 7 parameters, no output schema, and no annotations, the description is relatively brief. It covers core mechanics but omits details on several parameters and doesn't describe the return value or any side effects. It's adequate but not fully complete for complex usage.

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 only 43%, so the description must compensate for undocumented parameters like count, criteria, safe_search, and session_id. It adds meaning for feedback (referencing cell ids) and keywords (explicit replacement) but does not explain the remaining parameters. The description fails to bridge the coverage gap for those.

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 the tool's purpose: it iterates on an existing search session by taking feedback referencing round-qualified ids, producing the next round with dedup. It distinguishes from siblings by implying it's not for starting a new session (image_search_start) but for refinement, and the title reinforces 'existing'.

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?

It gives clear usage instructions: provide feedback with round-qualified ids and optionally explicit keywords. It implies when to use (with an existing session) but does not explicitly mention when not to use or name alternatives. Context from siblings suggests this is for continuation, but the description alone doesn't state exclusions.

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 burden of behavioral disclosure. It details the process steps, the return values (grid file path, selected ids, metadata table, keywords used), and explains special behaviors like the 'filter' parameter (false skips filter) and 'keywords' parameter (skips LLM parsing). It also notes the default for filter follows FILTER_MODE. This is transparent, though it does not mention session state persistence or file system side effects beyond returning a path.

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 concise sentences. The first enumerates the pipeline steps without redundancy, and the second lists the return values. It is front-loaded with the core action and contains no filler or repetitive language.

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 tool's behavior, parameters, and return values. It does not explain the overall session workflow (e.g., that image_search_iterate follows), but that is arguably outside the scope of a single tool description. The return list compensates for the absent output schema. Completeness is high for the tool's complexity.

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 83%, so most parameters are described in the schema. The description adds meaningful context beyond the schema by explaining that 'count' defaults to grid capacity, 'filter=false' skips the vision filter, and 'keywords' skips LLM parsing. It also clarifies the filter default via FILTER_MODE. This enriches the parameter understanding.

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 clear verb and resource: 'start an image search session.' It then describes the full pipeline (parse query, search parallel, dedupe, render grid, filter, return results). The action is specific and distinct from siblings like iterate, collect, and status, making it obvious this tool initiates 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 does not explicitly state when to use this tool versus its siblings. It does not mention 'use this to begin a session' or direct the agent to image_search_iterate for refinement. While the name implies it is the starting point, there is no explicit guidance on choosing it over alternatives or any exclusions.

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 bears full responsibility for disclosing side effects. It lists what data is returned but does not explicitly state that the operation is read-only or free of side effects. The verb 'show' implies a non-mutating action, but this is not made explicit, leaving some ambiguity.

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 a single sentence that front-loads the core purpose ('show session state') and then lists all contents in a compact list. There is no superfluous information, and every item contributes to understanding the returned data.

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 status tool with one parameter and no output schema, the description lists the key fields returned, which is helpful. However, it lacks an explicit read-only statement and does not mention error conditions (e.g., invalid session_id), which are important given the absence of annotations. It is adequate but not fully complete.

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?

The description completely ignores the only parameter, session_id, and the schema provides no description for it either. The agent gets no additional context about the format, origin, or purpose of session_id beyond its name, which is insufficient given the 0% schema description coverage.

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 the verb 'show' and the resource 'session state', and then enumerates the specific contents ('rounds so far, per-round selections/rejections, current keywords, and collected ids'). This distinguishes it from sibling tools that start, iterate, or collect, as it is the only one that reports on state.

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?

No guidance is given on when to use this tool versus its siblings. It does not mention that it should be used between iterations, nor does it reference alternatives or conditions that would select it. The only hint is the name 'status', which implies a read operation, but there is no explicit context.

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