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. It usefully discloses relative token cost per mode (10-30 / 200-400 tokens) and that results are cross-validated, but says nothing about read-only safety, required permissions, rate limits, or what a domain misconfiguration report actually contains.

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 purpose is front-loaded in the first clause and every sentence carries information about scope or mode selection. The ALL-CAPS labels and emoji add noise but cost little, and the mode guidance is dense rather than padded.

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?

With only two parameters, no output schema, and no annotations, the description covers the analysis scope and mode tradeoffs adequately. It is still thin on what the agent should expect to receive beyond token estimates — no mention of return structure, severity reporting, or what happens with the default 'example.com' domain.

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 both parameters are already documented and the baseline is 3. The mode explanations do add selection meaning beyond the schema's terse 'Response detail level', but they are invocation guidance rather than semantic enrichment of the field itself, and the domain parameter is left to 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 names a specific resource (email security) and the exact artifacts analyzed — SPF, DMARC, DKIM — plus the output shape (domain-by-domain breakdown with cross-validation). This clearly separates it from generic siblings like analyze_security_risks, though it never explicitly names a sibling alternative.

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 concrete selection criteria for the response_mode parameter ('minimal' for simple counts, 'standard' for an overview, 'detailed' for comprehensive analysis) with example questions. However, it offers no guidance on when to choose this tool over sibling analysis tools, and no prerequisites or 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?

No annotations are provided, so the description carries the full disclosure burden. It usefully discloses approximate token budgets per response mode (20-50, 200-300 tokens), which is genuine behavioral context. However, it never states that this is a read-only analysis operation, what permissions are needed, or any rate/scope 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?

Three compact sentences, front-loaded with the core purpose before the response-mode guidance. The emoji and ALL-CAPS headers are slightly noisy formatting, but every sentence carries information and nothing is 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?

There is no output schema, so the description should carry more of the return-value picture; it explains response verbosity but not the structure of the breakdown itself. Combined with the absence of annotations and any sibling routing, the definition is adequate but has clear gaps for a tool in a crowded analysis toolset.

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 goes beyond the schema by mapping each response_mode value to a concrete output size and content shape, adding meaning the enum alone does not convey. domain and focus_factor are left to the schema, which documents them adequately.

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?

States a specific verb+resource: 'Get detailed breakdown of security issues by specific types (SPF, DMARC, patching, etc.)'. The parenthetical examples make the resource concrete. It does not, however, differentiate itself from siblings like analyze_security_risks or analyze_email_security, so an agent must infer the boundary.

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 guidance for the response_mode parameter ('minimal' for counts, 'standard' for summary, 'detailed' for full breakdown), which is real usage context. But it offers no guidance on when to choose this tool over the many sibling analysis tools, so tool-level selection is left implied.

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. It implies a read-only analysis but never confirms it, and says nothing about required permissions, whether it accesses live data, rate limits, or what triggers a failure — only marketing-level claims of 'intelligent prioritization' and 'actionable guidance'.

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 sentence, but padded with an emoji and evaluative filler ('Comprehensive', 'intelligent', 'actionable') that doesn't help an agent decide or invoke. The core purpose is front-loaded, which saves it from being worse.

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 zero-required-param, read-only-style analysis tool with fully documented schema and no output schema, the description is minimally adequate. It omits the routing information (when this beats sibling analyzers) that matters most given eight siblings in the same space.

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 all three parameters (focus, domain, response_mode) including their enum meanings are already documented in the schema. The description adds no parameter-level detail beyond the vague 'flexible response modes', so baseline 3 applies.

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?

States a specific verb+resource (analyze security risks) and enumerates what it covers: critical vulnerabilities, risk patterns, remediation guidance. However, it never distinguishes itself from close siblings like analyze_email_security or security_dashboard, so an agent must guess which analyzer applies.

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 when-to-use, prerequisites, or alternatives are given. Phrases like 'flexible response modes' imply options but never state the conditions under which this tool should be chosen over the many sibling analyzers.

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 the dual return format (human-readable summary plus structured JSON), which is genuine behavioral information not present in the schema, and 'search' implies a read-only operation. However, it says nothing about auth requirements, result caps beyond the schema's limit, or pagination 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?

Two short sentences with no filler; the core action is front-loaded and the return-format sentence earns its place by clarifying output shape. Nothing is padded, though it is too terse to cover usage 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?

A 5-parameter, read-only discovery tool with no output schema and no annotations. The schema fully documents inputs, but the description leaves when-to-use and result-handling behavior unaddressed, so it is only minimally 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?

Schema description coverage is 100%, so tag, limit, query, method, and include_schema are already fully documented with examples and defaults. The description adds no parameter-level meaning beyond what the schema provides, which is the expected baseline of 3.

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?

States a specific verb+resource ('Search and discover SecurityScorecard API endpoints'), which is clearly distinct from the security-analytics siblings like analyze_security_risks or query_security_data. It never explicitly names an alternative, so sibling differentiation is implicit rather than stated.

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 on when to use this meta-discovery tool versus query_security_data or the other analysis tools, and no mention of prerequisites or what happens when a query returns nothing. The agent must infer usage entirely from the name.

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. It usefully discloses expected output size per mode (50-100, 300-500 tokens), which helps an agent budget context. It does not state whether the operation is read-only, whether it requires prior scan data, or any auth/rate-limit 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 body is short and front-loaded, but the '🎯 IMPROVEMENT PLAN:' and 'INTELLIGENT RESPONSES:' labels are decorative noise that restate the title and add no information. The three response-mode clauses do earn their 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?

For a zero-required-parameter, no-output-schema tool, the description covers the response_mode choice adequately but omits the workflow context an agent needs: whether this consumes prior analysis results, whether it is safe/read-only, and how it relates to analyze_security_risks or query_security_data. Minimum viable, with clear 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 description coverage is 100%, so the baseline is 3, but the description adds real meaning for response_mode by quantifying the token cost and giving a concrete example ('what should I fix first?'). domain, timeline, and target_grade are left entirely to the schema, but that is acceptable at full 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?

States a specific verb and resource: 'Generate security improvement recommendations,' reinforced by the title 'Security Improvement Plan'. It is clear what the tool produces, but it never distinguishes itself from siblings like analyze_security_risks or query_security_data, which an agent must choose between.

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 detailed guidance on choosing response_mode ('minimal' for simple questions, 'standard' for summary, 'detailed' for full roadmap), which is genuinely useful. However, it offers no guidance on when to use this tool versus the sibling analysis tools, and no prerequisites or sequencing 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?

No annotations are provided, so the description carries the full disclosure burden. It never states that this is a read-only operation, whether any authentication or scope is required, whether results are paginated, or how the 'security context' is sourced. 'Discover' implies a safe read but that is left to inference.

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?

Short overall, but padded with all-caps headers, an emoji, and a self-congratulatory 'INTELLIGENT RESPONSES' label that carry no information. The useful content (mode selection) sits after the fluff rather than being 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?

For a 3-parameter, zero-annotation, no-output-schema tool, the description covers response sizing well but omits the operation's safety profile and return shape, and the schema's placeholder default domain ('example.com') is unexplained. Enough to call the tool, but not enough to call it confidently.

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, but the description goes beyond the schema for response_mode: the schema only says 'Response detail level' while the description gives concrete token budgets (20-50 / 200-400 tokens) and matching question types. Domain and include_risk_details still get no extra meaning.

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?

States a concrete verb+resource ('Discover domains and IPs') and adds scope ('security context and data completeness validation'), so the agent knows this is an asset inventory operation. However it never distinguishes itself from close siblings such as api_discovery or validate_data_completeness, and the 'data completeness validation' phrase actively overlaps with the latter.

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 clear guidance for one parameter (which response_mode to pick for which question type), which implies the tool is for inventory/summary queries. It never says when to choose this tool over the sibling discovery or validation tools, so the alternative-selection guidance is absent.

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 but discloses only endpoint validation and parameter hints. It omits critical behavioral traits: authentication requirements, side effects of POST/PUT/DELETE, rate limits, error behavior, and whether calls are read-only or destructive.

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 front-loaded sentences with no filler, efficiently stating the core mechanism and validation features. It is appropriately sized for a short summary, though the first sentence is vague rather than wasteful.

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?

This is a complex tool with five parameters, no annotations, and no output schema, yet the description omits essential context: what security data is queried, how authentication works, what happens with mutating methods, and what the return format looks like. It is not complete enough for an agent to invoke confidently.

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 only a generic 'parameter hints' phrase, which does not extend parameter meaning beyond the schema; 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 description states 'Direct API access with smart endpoint validation,' which gives a general verb-and-mechanism but does not specify the resource (security data) or distinguish this tool from siblings like api_discovery. An agent can infer it performs API calls, but the actual purpose is vague.

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 alternatives such as api_discovery or validate_data_completeness. The description only mentions behavior ('Uses API discovery to validate endpoints'), not usage conditions or 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?

No annotations are provided, so the description carries the full behavioral burden. It mentions response modes and output detail levels, but does not state whether the tool is read-only, what permissions are required, whether there are rate limits, or how the security score is sourced or refreshed.

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 and front-loads the security status purpose before explaining response modes. It is efficient, though 'comprehensive' appears twice and the response-mode detail partly duplicates the schema.

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 two-parameter overview tool with no output schema and no annotations, the description states the output content and response modes, but it omits selection guidance versus siblings and behavioral context such as read-only safety. It is adequate but leaves clear 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 description coverage is 100%, so both domain and response_mode are already fully documented in the input schema. The description repeats the concept of response modes but adds no new parameter meaning beyond what the schema provides, making the baseline 3 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 has a clear verb ('Get') and resource ('security score, grade, and key metrics'), so an agent knows this returns a security dashboard summary. It identifies itself as an overview, but does not explicitly differentiate from sibling tools like query_security_data or analyze_security_risks.

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 mode-based usage guidance ('minimal responses for quick queries and detailed analysis for comprehensive security overviews'), but this is about the response_mode parameter, not when to choose this tool over its siblings. No alternative tools are named or compared.

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 usefully discloses output size per mode (25 vs 200-400 tokens), which is genuine behavioral context, but says nothing about whether the operation is read-only, what it costs, or what happens on failed validation.

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?

Three compact sentences with the core action front-loaded. The emoji and the ALL-CAPS 'INTELLIGENT RESPONSES' header are marketing noise that costs a little signal, but nothing is padded or 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?

With no annotations and no output schema, the description must explain what validation produces and how the three parameters interact. It covers response_mode well but leaves domain and expected_asset_count semantics and the shape of the validation result unaddressed.

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, but the description adds real value beyond the schema by quantifying what each response_mode returns (25 tokens for minimal, 200-400 for standard, full audit for detailed). It leaves domain and expected_asset_count entirely to 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?

States a specific verb and resource: 'Cross-validate tool results for accuracy and completeness.' An agent can tell this is a validation tool, though the phrase 'tool results' is vague about which inputs it consumes and nothing distinguishes it from siblings like analyze_security_risks or query_security_data.

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 the response_mode options but never says when to invoke this tool versus the eight sibling analysis tools, nor what prerequisite data must exist. The 'Use minimal/standard/detailed' lines are parameter guidance, not usage guidance.

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