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 parallel lookups, which is a useful behavioral trait. However, it does not mention data freshness, authentication needs, rate limits, or potential side effects. Given the mutation-like nature of comparison tools, more transparency could be warranted.

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 (about 60 words) with no wasted words. It front-loads the core purpose, then adds behavioral detail and use cases. Every sentence 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?

The tool is moderately complex (multi-company, multiple signals), and the description covers input, signals, derived outputs, parallel execution, and use cases. Given an output schema exists, the description does not need to explain return values but still provides sufficient context 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?

The input schema has one parameter with 100% description coverage. The description adds value by clarifying the parameter as 'ticker symbols or CIKs' and reinforcing the 2-5 range. It also explains how the parameter is used to generate derived winners, enriching 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 tool compares 2-5 companies across specific SEC disclosure signals, listing each signal and noting it returns derived 'winners.' This specific verb+resource combination distinguishes it from single-company sibling tools like get_company_filings_summary.

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 suggests use cases ('competitive intelligence or risk triage across a watchlist') and specifies the input range (2-5 tickers). It implicitly differentiates from siblings, but lacks explicit exclusions or when-not-to-use 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?

Despite no annotations, the description fully explains the tool's read-only behavior and output. It details the returned signals and their nature, making the agent aware of what to expect. No side effects are implied.

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, well-structured paragraph that front-loads the main action and lists outputs efficiently. 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 the simple single-parameter input and existing output schema, the description covers all necessary context: what it returns, key signals, and its role as a first-pass tool. It is complete for an agent to decide 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 100%, so the baseline is 3. The description does not add further parameter guidance beyond the schema's description. It is adequate but not enhanced.

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 retrieves a structured overview of SEC filing activity, listing specific outputs (recent 20 filings, velocity, material event count, etc.). It distinguishes itself from siblings by positioning as a first-pass signal before insider or material event detail.

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 advises using this as a first-pass signal before deeper tools, providing clear context. It does not explicitly list when not to use, but the guidance is strong enough.

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 full burden. It discloses that directional signals are null/0 in v0.1 and mentions returns (references and counts). It lacks details like auth or rate limits, but for a read-only probe this 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?

The description is concise: two sentences plus a note. It is front-loaded with purpose, then returns, then limitation. 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?

Given the tool's simplicity (2 params, output schema present), the description covers purpose, returns, and a key limitation. No gaps remain for typical 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 100%, so the schema already explains parameters well. The description mentions configurable lookback but adds no new semantic meaning beyond the schema's 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 description specifies the verb 'Probe' and resource 'insider filing activity' with clear forms (3, 4, 4/A) and a configurable lookback window. It answers a direct question and states returns. It differentiates from siblings like get_institutional_signal by focusing on insider filings.

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 for recent insider filing activity but does not explicitly state when not to use or compare with alternatives. The note about v0.2 hints at limitations, but no direct guidance on preferring other tools.

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 the burden. It discloses that institutional_signal and recent_13f_count are null/0 in v0.1, and explains the activist_risk_flag logic. This provides important behavioral context beyond 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?

The description is two concise sentences plus a note, front-loading the main purpose and providing essential details without waste. 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?

Given the presence of an output schema (not shown), the description adequately covers key outputs and version caveats. It lacks error handling info but is sufficient for a tool of this 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 description coverage is 100%, so the baseline is 3. The description adds minimal new semantics beyond the schema, merely restating the parameters in context. It does not compensate for low 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 it probes institutional and activist investor signals for a company, listing specific outputs like activist_risk_flag and 13D filings. It distinguishes from siblings like get_insider_signal by focusing on institutional actions.

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 explains what the tool does but does not provide explicit guidance on when to use it versus sibling tools like compare_disclosure_signals or get_company_filings_summary. Usage context is implied but not directly addressed.

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 behavior. It explains the output includes severity tags, redflag_count, and category_counts, and mentions that events are tagged with item codes mapped to labels. It does not specify permissions, rate limits, or error cases, but provides sufficient detail about the tool's function and output.

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, front-loading the main purpose and then adding details on output format, example question, and pricing. It is not overly verbose; each sentence serves a purpose. Minor room for improvement but overall concise.

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 presence of an output schema (though details not provided to us), the description is fairly complete. It covers the tool's purpose, output (redflag_count, category_counts), and an example use case. It does not discuss error handling or limits, but it adequately sets expectations for a digest 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning to the parameters beyond what the schema already provides (ticker_or_cik and lookback_days). It focuses on the output and use case, not parameter details, so no extra value is given.

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 identifies the tool as retrieving a severity-ranked digest of 8-K and 8-K/A filings, specifying the resource (filings), action (retrieve digest), and output format (tags, severity levels, counts). It also provides a concrete example question, distinguishing it from sibling tools like get_insider_signal or get_company_filings_summary, which focus on different data types.

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 providing an example question about recent cybersecurity incidents or restatements, and notes it is a premium-tier tool with per-call cost. However, it does not explicitly compare to sibling tools or state when not to use it, leaving room for ambiguity in tool selection.

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