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

No annotations exist, so the description carries the full burden. It discloses configuration retrieval, connection testing, API key masking, and a 10-second timeout. However, it does not describe failure modes or response structure in detail.

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, well-structured with bullet points, and front-loaded with the main purpose. Every sentence adds value without redundancy.

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 parameters, output schema, or annotations, the description covers the tool's main functions and security. It could be more informative about error handling or response format, but it is largely complete for its purpose.

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?

There are no parameters, and schema coverage is 100%. The description adds value by explaining what the tool does beyond the empty schema, contextualizing its purpose and behavior.

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 returns the current server configuration and tests upstream connectivity, using specific verbs and resources. It distinguishes itself from sibling tools like web_search or get_sources by focusing on diagnostics.

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?

Explicit guidance: 'Use this tool first when debugging connection or configuration issues.' This tells the agent exactly when to invoke it, along with edge cases and best practices.

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 of behavioral disclosure. It conveys this is a read-only retrieval of cached sources, which is inherently safe, and hints that data persists ('cached'). It does not mention what happens for invalid/expired session_ids, auth requirements, or pagination, but for a simple retrieval tool the basic safety profile is adequately conveyed.

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 highly repetitive — three sentences effectively say the same thing: use the web_search session_id to get the source list. It also contains a typo ('invoke the this tool'). A single crisp sentence ('Retrieve all cached sources for a prior web_search call using its session_id.') would carry the full meaning. The redundant first sentence should be cut.

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?

An output schema exists, so the return format is covered externally. For a low-complexity tool with a single required parameter, the description adequately covers when to use it (after web_search) and what it returns (the full source list). The main gaps — error behavior for invalid sessions and any filtering/ordering — are minor given the tool's simplicity.

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% — the schema already documents session_id as 'Session ID from previous web_search call.' The description reinforces that the ID must come from web_search, adding marginal provenance context, but it does not add meaningful syntax or format details beyond what the schema provides. 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 core purpose is clear: 'Retrieve all cached sources for a previous web_search call' states a specific verb and resource, and ties the tool to the web_search sibling via session_id. However, the opening sentence uses odd emotional framing ('When you feel confused or curious...') which muddies the definition rather than clarifying it. The purpose is distinguishable from siblings like web_fetch and web_map because it targets cached search sources.

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 useful context: the tool is invoked with a session_id returned by a prior web_search call, so it is clearly a follow-up to web_search. However, it never states when NOT to use it or names alternatives (e.g., web_fetch for fetching actual page content). The 'confused or curious' trigger is too vague to be actionable guidance.

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 the full burden. It discloses a key behavioral trait: the level controls which phases run. However, it does not mention side effects like storing plan state, requiring a session_id from plan_intent, or the ability to overwrite via is_revision. These gaps prevent a higher score.

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 sentences with zero waste. The phase identification is front-loaded, and the level-to-phase mapping is stated concisely. Every word earns its place.

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 8 parameters, no outputs schema, and no annotations, the description is incomplete. It explains the level's impact but does not describe the tool's return value, the requirement for a prior plan_intent session, or how downstream tools use this output. The phase mapping is useful but not sufficient for full contextual understanding.

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 meaning beyond the schema by explaining the level parameter's effect on phases (Level 1 = phases 1-3, etc.). This is valuable semantic content not present in the schema's simple 'Complexity 1-3'. Other parameters remain adequately documented by the 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?

The description clearly states the verb 'Assess' and resource 'search complexity' with an explicit range (1-3). It also identifies itself as 'Phase 2', which differentiates it from sibling tools like plan_intent (Phase 1) and plan_execution (later phase). The mapping of levels to phases adds specificity.

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 provides clear context by labeling this as 'Phase 2' and explaining that the level 'Controls required phases', implying when it should be called (after plan_intent) and its consequence. However, it does not explicitly mention when not to use it or name alternatives, so it falls 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.

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It explains the input format for parallel_groups but does not disclose side effects (e.g., whether this overwrites a previous plan when is_revision is true), requirements like authentication, or what the tool does after defining the order. The description is purely about the input syntax, not the behavior.

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 with zero wasted words. It leads with the purpose ('Phase 6: Define execution order') and immediately provides the critical formatting detail for parallel_groups. The example is compact and directly relevant. This is an appropriately sized, front-loaded description.

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 tool has no output schema and no annotations, the description leaves out essential context: what the tool returns, prerequisites (like the session_id provenance), and how this fits into the broader planning flow. It only explains the input format, which is insufficient for an agent to safely and correctly call it without additional assumptions.

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 seven parameters. The description adds a slightly different example ('sq1,sq2;sq3' vs the schema's 'sq1,sq2;sq3,sq4') and restates the semicolon/comma rule, but this is marginal added information. Since the baseline with full coverage is 3, the description meets it but does not elevate beyond the 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?

The description states a clear verb and resource: 'Define execution order' and identifies it as 'Phase 6' of a planning process. It provides a concrete format example for parallel_groups, which makes the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like plan_tool_mapping or plan_sub_query; the distinction is only implied by the 'Phase 6' context.

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 no explicit guidance on when to use this tool versus alternatives. It does not state preconditions (e.g., 'requires a session_id from plan_intent') or any exclusions. The 'Phase 6' label implies a sequential step, but there is no mention of when this should be invoked or what situations call for a revision.

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 are absent, so the description must carry the burden. It states it creates a session and returns session_id, but does not disclose side effects such as overwriting existing intent (though the is_revision parameter exists in the schema). The description doesn't mention idempotency, revision behavior, or any destructive implications. It's adequate but not fully transparent.

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 yet information-dense. It front-loads the purpose in the first sentence, then presents the pipeline flow and complexity rules in a clear, scannable format. There is zero redundancy; every sentence contributes necessary context.

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 tool's role in a multi-phase pipeline, the description covers the essential context: it is the entry point, it returns session_id, and it specifies the full flow and complexity-based phase requirements. It does not address the revision use case (session_id revision) that the schema supports, but the schema covers that. Overall it is complete for the typical agent workflow.

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 is 3. The description does not add any parameter-specific meaning beyond what the schema already documents. It doesn't mention any of the input fields (thought, core_question, query_type, etc.) or their roles. Thus it adds no extra value over the 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?

The description states the exact purpose: 'Phase 1 of search planning: Analyze user intent' and that it creates a session and returns session_id. It clearly differentiates from sibling tools by being explicitly 'FIRST' in the required flow, which is listed. This is specific and unambiguous.

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 explicitly says 'Call this FIRST to create a session' and provides the full required flow (plan_intent → plan_complexity → ...). It also gives conditional guidance based on complexity levels (Level 1, 2, 3), which tells the agent when to expect which subsequent phases. This is clear usage guidance with no ambiguity.

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 full burden. It discloses key behavioral constraints (term length, purpose reference, one term per purpose/round) and clarifies that approach and fallback_plan are strategy-level. Some behaviors like error handling or side effects are absent, but the description is sufficiently transparent given the complexity.

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: a one-line summary followed by structured bullets. It front-loads the main purpose and delivers key rules efficiently. No unnecessary words or repetition.

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 thoroughly covers the core parameter (terms_json) but does not explain the purpose of other parameters like thought, confidence, or is_revision beyond what the schema provides. Given the tool's role in a workflow, some of these may be self-explanatory, but the description could add more context.

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 by specifying the exact shape of terms_json (object with term, purpose, round) and rules. It also clarifies that approach and fallback_plan are top-level params, not inside terms.

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: submit all search terms in one batch call (Phase 4). It uses specific verbs and resources, but does not explicitly differentiate from sibling tools like plan_sub_query or plan_intent.

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 implicit usage context (Phase 4, batch submission) and provides rules for terms (≤8 words, purpose must reference sub-query id). However, it lacks explicit guidance on when not to use the tool or when alternatives are preferred.

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 exist, so description carries full burden. It discloses batch submission, validation rules (unique ids, no cycles), error on duplicate, and is_revision effect. However, missing details on result behavior (e.g., return value, idempotency).

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?

Description is well-structured with bullet points and a JSON example. Front-loaded with purpose. Could be slightly more concise by omitting standard validation details, but overall 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?

No output schema exists; description does not explain return values or error responses. Prerequisites are implied by required session_id from plan_intent. Missing post-submission context (e.g., success indication, session state changes).

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 covers 100% of parameters. Description adds significant value for items_json by specifying exact JSON shape, validation constraints, and the purpose of is_revision. Other parameters (session_id, thought, confidence) are not enhanced beyond schema, but the critical parameter is well-explained.

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 tool submits ALL sub-queries in one call (batch). Verb 'submit' and resource 'ALL sub-queries in ONE call' are specific. Mention of 'Phase 3' distinguishes it from earlier planning phases.

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?

Only implies phase context ('Phase 3'), but no explicit when-to-use or when-not-to-use. No comparison to sibling tools like plan_intent or plan_execution. No guidance on choosing is_revision vs not.

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 provided, and the description does not disclose behavioral traits like side effects, authorization needs, or rate limits. The minimal description lacks transparency beyond the basic purpose.

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 extremely concise with two sentences. The first sentence states the purpose clearly, and the second provides the exact JSON template. No wasted words.

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 the core element (mappings_json format) but lacks information on response behavior, validation, or error handling. It is adequate but not comprehensive.

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%, but the description adds value by providing the exact JSON structure for mappings_json, which goes beyond the schema's generic description. This helps the agent format the parameter correctly.

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 'Submit' and the resource 'all sub-query → tool mappings in one call (batch)'. It distinguishes from sibling tools like plan_sub_query and plan_execution by specifying it's a batch mapping submission.

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 says 'Phase 5' and 'Submit ALL sub-query → tool mappings in ONE call', indicating when to use it. However, it does not explicitly state when not to use it or provide alternatives, though sibling tools give context.

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 fully discloses behavior: the change takes immediate effect, persists to ~/.config/selvin-search/config.json, and invalid model IDs may cause API errors in subsequent requests. This is complete transparency for a mutation 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?

The description is well-structured with 'Key Features' and 'Edge Cases' sections, front-loading the core purpose. It is slightly verbose with some redundancy (e.g., 'Model Selection' and 'Immediate Effect'), but every sentence adds value.

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 one-parameter tool with no output schema, the description covers all necessary context: what the tool does, how it persists, prerequisites (model ID from get_config_info), and consequences of invalid input. It is self-sufficient.

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% with a clear description for the 'model' parameter. The description adds value by linking to get_config_info for valid IDs and explaining the context (search summarization), going beyond the schema alone.

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: switching the GLM-compatible model used for search summarization and persisting the setting. It differentiates from siblings by specifying the domain (search summarization) and persistent configuration, distinguishing it from informational tools like get_config_info.

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?

Explicit best practices are provided: use get_config_info to verify available models before switching, warning about invalid model IDs causing subsequent errors, and noting persistence across sessions. This gives clear guidance on when and how to use the tool.

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?

Despite no annotations, the description thoroughly discloses caching behavior, planning gate enforcement, return fields, and cache-hit detection, covering all major behavioral traits.

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?

Well-structured with clear sections, each sentence adds meaningful information without waste, and front-loaded with the core purpose.

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, describes return fields adequately. Covers planning integration, caching, and platform filtering, making it complete for a search tool in this context.

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 3. Description adds value by explaining the plan_session_id gating, platform focus, and model override context, going beyond schema 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?

Clearly states it performs web search and caches results, distinguishing from sibling tools like get_sources which retrieves full source list.

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 describes the PLANNING GATE behavior and when to use empty plan_session_id for one-shot lookups, providing clear context for when this tool is appropriate vs alternatives.

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