pentest-mcp-server

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, non-mutating operation. The description adds value by disclosing what the tool produces: structured findings covering specific categories (version disclosures, stack traces, debug headers, internal paths, authentication patterns, CORS configuration, detection signals, remediation, and methodology vectors). This goes beyond the annotations by describing the output structure and scope. 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 a single, dense paragraph that front-loads the core purpose ('Analyze an HTTP response from authorized probing') and then lists the finding categories. It's efficient with no filler words. The list of categories is somewhat long but each item adds value by clarifying the tool's scope. Could be slightly more structured (e.g., bullet points) but is acceptable as prose.

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 has an output schema (not shown in detail but indicated by 'Has output schema: true'), which likely describes the structured findings. The description covers the input parameters (via schema) and the output categories. The description mentions 'remediation' and 'methodology vectors' which are important for a pentest tool. Given the complexity of a security analysis tool, the description is reasonably complete. It could mention that the tool is read-only (though annotations cover that) or provide more detail on how the analysis works, but the current level is adequate.

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 four parameters (context, status_code, response_body, response_headers) are already well-documented in the schema. The description doesn't add parameter-specific semantics beyond what the schema provides. The description mentions 'context' narrows pattern matching, which aligns with the schema's description, but doesn't add new information. Baseline 3 is appropriate given full schema 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 tool's purpose: analyzing HTTP responses from authorized probing for information leakage, fingerprinting signals, and related exposure. It lists specific categories of findings (version disclosures, stack traces, debug headers, etc.), which distinguishes it from sibling tools like pentest_generate_payloads or pentest_map_techniques. The verb 'analyze' and resource 'HTTP response' are 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?

The description implies usage context: it's for analyzing responses from authorized probing, which suggests it should be used after sending requests. It doesn't explicitly state when not to use it or name alternatives, but the sibling tools are clearly different in function (encoding, payload generation, lookup, mapping). The 'authorized probing' qualifier provides important usage context. However, it doesn't explicitly say 'use this when you have a response to analyze' or contrast with alternatives.

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?

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses that all transforms are local and no live probing occurs, which reassures about network safety. It also outlines the output contents (final value, intermediate values, optional decode path, rationale, detection guidance), providing transparency about what the tool returns. No contradictions 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 compact, consisting of two sentences that efficiently convey the core action and key details. It front-loads the verb and resource, then lists output features and safety notes without unnecessary elaboration. No filler or redundant phrasing.

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 schema with full descriptions and annotations indicating read-only and idempotent behavior, the description covers the tool's purpose, output, and safety. It does not delve into edge cases or error handling, but that is acceptable as the output schema likely describes the return format. The description is self-sufficient for an agent to decide when and how to invoke the 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 schema already provides detailed descriptions for all three parameters (payload, chain, explain), including examples and constraints. The tool description does not add significant extra meaning to these parameters; it mostly reiterates the output structure. Since schema coverage is 100%, the baseline is 3, and the description does not elevate it further.

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 function: transforming a payload string through an ordered encoding chain. It specifies the verb ('Transform') and the resource ('payload string'), and adds context with 'for authorized filter research.' This distinguishes it from sibling tools like payload generation or response analysis, though it does not explicitly name alternatives.

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 conveys when to use the tool implicitly: when encoding a payload for filter research. It includes a safety note ('All transforms are local; no live probing occurs') that hints at usage boundaries. However, it does not explicitly compare with sibling tools (e.g., 'use pentest_generate_payloads for creation'), leaving some ambiguity about when this tool is preferred over alternatives.

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 readOnlyHint=true and idempotentHint=true, covering safety and deterministic output. The description adds valuable detail about what each template includes (category, rationale, detection signature, mitigation, optional research note and encoded variant), which is beyond annotations and helps agents understand output structure.

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, efficient sentence that front-loads the primary action and scope, then briefly enumerates output contents. Every clause earns its place with no redundancy or filler.

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 complexity (5 parameters, enums, output schema present), the description provides enough context about the returned templates and ties to the 'context rationale' element. It does not explicitly mention parameters like count or encoding, but those are fully documented in the schema, and the output schema is present, so nothing critical 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 description coverage is 100%, so the description does not need to elaborate on parameters. It adds no parameter-specific details beyond the schema, and the baseline of 3 is appropriate when schema carries the full load.

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 verb ('Generate') and resource ('context-specific payload templates'), with a scope qualifier ('for authorized systems'). It is easily distinguished from siblings like pentest_analyze_response (analysis) or pentest_encode (encoding), so an agent knows exactly what this tool does without opening the schema.

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 implicitly frames usage as part of an authorized pentest workflow, but does not explicitly state when to prefer this tool over alternatives such as pentest_guide or pentest_map_techniques. The context is clear, yet exclusions or alternative routing are left to inference.

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 establish readOnlyHint=true and idempotentHint=true, so the agent knows this is a non-mutating, repeatable operation. The description adds value by disclosing that the returned content is an 'authorized-testing' playbook that covers phases (recon, enumeration, exploitation, post_exploitation) and includes elements like detection signals, mitigations, and 'context-derived tool suggestions.' This goes beyond the annotations by describing the nature of the output without contradicting them.

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, information-dense sentence that front-loads the core action and resource, then enumerates the coverage without redundancy. Every phrase contributes (phases, objectives, techniques, detection signals, mitigations, pitfalls, references, tool suggestions). It is compact yet comprehensive, making efficient use of the word budget.

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 that an output schema exists (as indicated), the description does not need to explain return formats. The description covers all key aspects: the action, the resource, the scope (15 vectors), optional narrowing, and the content of the playbook. For a read-only, idempotent tool with full schema coverage, this is complete. An agent has enough information to invoke it correctly without ambiguity.

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 provides full coverage (100%) for all three parameters, including enums and descriptions for vector and phase, and property-level descriptions for the target_context object. The description simply restates the existence of a 'selected vector' and 'optional target context,' adding no new meaning beyond the schema. Given the high schema coverage, a baseline of 3 is appropriate; the description does not compensate or enrich parameter semantics.

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 function: 'Return an authorized-testing methodology for a selected vector and optional target context.' It identifies the specific resource (methodology) and the action (return), and specifies that it covers a full set of phases. This clearly distinguishes it from sibling tools like pentest_generate_payloads or pentest_analyze_response, which have narrowly scoped purposes.

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 its usage context: it is for retrieving a methodology for a vector, optionally narrowed by target context. However, it does not explicitly state when to prefer this tool over its siblings, nor does it name any alternatives. There is no 'when-not-to-use' guidance or comparison to pentest_map_techniques or pentest_lookup_technique. The usage context is inferable but not explicit, so it falls short of a 4.

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 readOnlyHint=true and idempotentHint=true, covering safety and repeatability. The description adds value by specifying what the result contains (identity, aliases, type, description, techniques with procedure-level context), and it notes the query fallback from exact ID to best-match on name/keyword. There is no contradiction with annotations, and the added behavioral detail is useful 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 two concise sentences, front-loaded with the core action and resource, then clarifying the accepted input formats and the nature of results. Every sentence earns its place, and there is no redundant repetition of the tool name or schema details.

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 single-parameter lookup tool with no nested objects and an output schema present (as per context signals), the description covers the purpose, input formats, and return content. The agent has everything needed to decide when to invoke it and what to expect, and the annotations cover side effects. Nothing essential 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% for the single 'query' parameter, so the schema already documents the parameter fully. The description adds extra semantic nuance: ID lookup is exact and case-insensitive, while name/keyword search returns the best match. This exceeds the baseline for high schema coverage and helps the agent understand query behavior without opening 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 specific action ('Look up') with a clear resource ('MITRE ATT&CK threat group or software entry') and the input modes ('ID, name, or keyword'). It differentiates from the sibling pentest_lookup_technique by focusing on groups/software rather than techniques, and it enumerates the returned fields, so an agent can tell exactly what the tool does.

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 implies when to use this tool: when looking up threat groups or software entries from ATT&CK. It implicitly distinguishes from pentest_lookup_technique by the resource type, but it does not explicitly state 'use this for groups/software, not techniques' or mention any exclusions. Given the sibling names, the context is clear enough without explicit exclusion.

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 establish read-only and idempotent behavior. The description adds a brief summary of the result contents (tactics, platforms, detection data, etc.), but since an output schema exists, this enumeration adds only moderate value beyond the structured 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 a single front-loaded sentence that hits the action first and then lists the result fields. The enumeration is somewhat long, but each item is meaningful and contributes to a complete overview.

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, fully documented schema, existing output schema, and read-only idempotent annotations, the definition is complete for an agent to invoke it correctly. Nothing essential for making the call 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 description coverage is 100%, with rich detail on the query parameter (examples, exact vs. best-match behavior) and include_subtechniques (default and when to disable). The description itself adds no parameter-level meaning beyond what the schema already provides.

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 ('look up'), a distinct resource ('MITRE ATT&CK technique'), and the two accepted input modes ('exact ID or keyword'). This clearly distinguishes it from the sibling pentest_lookup_group without requiring the agent to open either schema.

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 no explicit when-to-use or when-not-to-use guidance, nor does it reference any sibling tool. The only usage hint appears inside the include_subtechniques parameter schema, not in the description itself.

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 this as a read-only, idempotent operation, so the description does not need to repeat safety traits. It adds useful behavioral context by explaining the output includes relevance, detection opportunities, mitigations, and methodology vectors, though some of this is redundant with the existing output schema. It does not clarify whether this is a local knowledge-base ranking rather than a live scan, but the 'authorized target profile' framing partially signals a planning-oriented operation.

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, front-loading the verb, resource, and target context. The phrase 'associated methodology vectors' is somewhat vague and imprecise, which keeps it from being perfectly concise, but overall 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?

Given the output schema exists and input schema fully documents parameters, the description covers the essential invocation context well. It does not mention behavior when no profile parameters are provided, but because all parameters are optional and the schema documents defaults, this is a minor omission rather than a critical gap.

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%, and the schema already documents every parameter including defaults and enum constraints. The description restates four of the five profile dimensions (stack, services, auth_type, os) but adds no new semantic detail beyond what the schema provides, matching the baseline for high schema 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 names a specific verb ('Rank') and a precise resource ('ATT&CK techniques and OWASP test cases'), then scopes it to a target profile composed of concrete dimensions. This clearly separates it from siblings like pentest_lookup_technique and pentest_generate_payloads by indicating a multi-technique prioritization operation rather than a single lookup or payload construction.

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 provides clear situational context: use when you need profile-specific ranking of attack techniques and test cases against a target's stack, services, auth type, and OS. It does not explicitly name alternatives or state when not to use it, but the described use case is unambiguous enough for an agent to select it correctly.

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