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

No annotations are provided, so the description must disclose behavior. It mentions extraction, pattern detection, and enrichment but does not reveal whether the operation is read-only, performance impacts, or failure modes. It is adequate but lacks depth.

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 extraneous information. The first sentence introduces the core functionality, and the second adds details on patterns and enrichment. It is front-loaded and 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?

With no output schema and no annotations, the description leaves gaps: it does not describe return values, prerequisites (e.g., file must be PE), or that enrich_from_db requires a built DB. Overall, it is moderately 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 coverage is 100%, so baseline is 3. The description adds value by explaining that detect_patterns includes injection/evasion/persistence patterns with MITRE mapping, and enrich_from_db adds API definitions from a knowledge base. This goes beyond the 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?

The description clearly states it provides detailed PE import analysis, extracting imports, detecting patterns with MITRE ATT&CK mapping, and optionally enriching with API definitions. This verb+resource specification distinguishes it from siblings like api_detect_patterns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternative tools like api_detect_patterns or other analysis tools. The description does not specify prerequisites, exclusions, or contextual triggers.

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?

The description discloses the detection focus and output type but lacks details on potential side effects, performance, or whether it is a read-only operation. Without annotations, it partially covers 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?

Two sentences with no superfluous words. The main action is front-loaded, making it efficient for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core purpose and output for a simple single-parameter tool. It could be improved by mentioning return format or error conditions, but it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides a clear description for the only parameter (file_path). The description adds no additional semantic context beyond what is in 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 explicitly states the tool detects injection/evasion/persistence API patterns from PE imports and outputs matched patterns with MITRE ATT&CK IDs and risk levels. This clearly differentiates it from siblings like api_analyze_imports.

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 PE file analysis but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any 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 burden. It describes what the tool returns and that it supports wildcards, but does not mention safety, idempotency, rate limits, or other behavioral traits typical for a lookup tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences. The first defines action and result, the second adds an important feature (wildcard support). No redundant information.

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 lookup tool with two well-described parameters and no output schema, the description fully explains what the tool returns and its functionality. No gaps given the 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%, but the description adds value by explaining that the api_name parameter supports wildcards and specifying the returned information categories, which is not in 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 looks up Windows API definitions from a knowledge base, listing the returned fields (signature, params, DLL, category). It distinguishes from siblings like api_search_category and api_analyze_imports.

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 mentions wildcard support but does not provide explicit guidance on when to use this tool versus siblings or when not to use it. Usage is implied but not clearly differentiated.

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, and the description does not disclose behavioral traits such as being read-only, potential side effects, or safety. For a search tool, transparency is limited; the agent cannot infer whether the operation is safe or has rate limits.

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—two sentences that immediately convey purpose and provide a concrete example. No extraneous words or superfluous 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 simple search tool with two parameters and no output schema, the description adequately covers core functionality. It explains the hierarchical category concept but could briefly mention that the 'limit' parameter controls maximum results (though the schema already includes a default).

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 100% parameter description coverage. The description adds value by explaining the hierarchical nature of categories with an example, which supplements the schema's 'Category path or substring' description.

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 action ('Browse/search') and the resource ('Windows APIs by category') with an illustrative example of hierarchical paths. It effectively distinguishes this tool from sibling tools like 'api_lookup' which are not category-focused.

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 the tool is for category-based browsing or searching but does not provide explicit guidance on when to use it versus alternatives like 'api_lookup' or other search tools. No when-not or exclusion criteria are given.

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 must disclose behavior. It states it returns detailed call records for a range, implying it is a read operation. However, it does not mention performance implications, whether it modifies state, or what 'detailed' means. Basic transparency but missing depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first states purpose, second gives use case. Every word earns its place. No redundancy or fluff.

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 no output schema, so the description should fully explain return values. It only says 'returns detailed call records,' which is vague. Additionally, the process_index parameter is not mentioned, leaving the agent without guidance on multi-process scenarios. Incomplete for a tool with 5 parameters.

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 baseline is 3. The description does not add new parameter semantics; it simply restates the range concept already captured in the schema. No additional meaning beyond 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 gets a context window of API calls around a specific index, which is a specific verb+resource. It implicitly distinguishes from siblings like apmx_get_calls (which likely returns all calls) and apmx_get_call_details (single call details) by focusing on a range.

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 a clear use case: 'useful for understanding what happened immediately before and after a suspicious call.' While it does not explicitly exclude other scenarios or name alternatives, the context is clear enough for an AI agent to decide when to use this 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?

No annotations are present, so the description carries the burden of disclosing behavior. It explains that the tool identifies handle producers and consumers and reveals attack chains. It does not mention any side effects, authentication needs, or limitations, but the described behavior is consistent with a read-only analysis tool. A score of 4 reflects adequate transparency without 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 extremely concise, consisting of two sentences that are front-loaded with the core purpose and supplemented with concrete examples. Every word serves a purpose, 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?

While the description explains the tool's functionality well, it omits important contextual details: the output format is not described (no output schema), and prerequisites like prior parsing with apmx_parse are not mentioned. For a tool with moderate complexity, this gap lowers completeness.

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?

All parameters have descriptions in the input schema, achieving 100% coverage. The description adds value by explaining the purpose of target_apis and limit, and giving context about default behavior. The schema handles the basic definitions, but the description enriches understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: tracking handle values across API calls to reconstruct operation chains. It provides specific examples of handle-producing and consuming APIs, and distinguishes itself from sibling tools by focusing on handle correlation rather than generic call listing or pattern detection.

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 analyzing API sequences related to handle usage, with examples of attack chains. However, it does not explicitly state when to avoid this tool or provide alternatives among siblings. The context is clear but lacks explicit usage boundaries.

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, description carries full burden. It discloses analysis behavior, use of MITRE ATT&CK, and outputs (risk level, timeline). Does not mention side effects (likely read-only) or performance, but is sufficient for a stateless analysis tool. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with front-loaded main action, followed by context on MITRE and output. Every sentence adds value; no unnecessary 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 no output schema, description adequately describes output (risk level, suspicious call timeline). Complexity is low with two parameters, one required. Context is sufficient for an agent to invoke correctly.

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% (both parameters described). Description adds no additional meaning beyond schema (file_path and process_index descriptions are clear). Baseline 3 assigned as schema carries the 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?

Description clearly states the tool detects injection/evasion/persistence patterns in APMX captured API calls, uses MITRE ATT&CK IDs, and returns risk level and timeline. This is a specific verb+resource that distinguishes it from siblings like api_detect_patterns (API-focused) and apmx_get_calls (raw calls).

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?

Description implies use for analyzing APMX captures for known attack patterns but does not explicitly state when to use this tool vs alternatives (e.g., apmx_injection_info for injection-only analysis, api_detect_patterns for API patterns). Lacks when-not-to-use or prerequisite 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 carries the full burden. It discloses key behaviors: shows pre/post parameter values, identifies return values, and extracts embedded strings. However, it does not explicitly state that the tool is read-only (e.g., analyzing a capture file) or discuss performance implications.

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 extraneous information. The first sentence defines the purpose, the second provides parameter usage guidance. It is front-loaded and 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?

Given the complexity (6 parameters, no output schema, no annotations), the description is reasonably complete. It covers the tool's output (parameter values, return values, timestamps) and parameter usage. However, it could mention error handling or limitations (e.g., file path validity) to be fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining how to use call_indices and api_filter, but it does not provide additional semantic detail beyond the schema's own 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 clearly states the tool extracts detailed API call records with parameter values, return values, and timestamps. It uses a specific verb (Extract) and resource (detailed API call records), distinguishing it from sibling tools like apmx_get_calls (which lists calls) and apmx_search_params (which searches parameters).

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 usage guidance: 'Use call_indices for specific records or api_filter to search.' This helps the agent decide which parameters to use. However, it does not explicitly differentiate when to use this tool over siblings like apmx_get_calls for listing vs. details.

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. Description implies read-only operation, but lacks details on performance, error handling, or side effects. Adequate but could be more explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences cover key purpose and behavior. No unnecessary words, front-loaded with core functionality.

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; description partially explains return records ('top-level API and nested calls'). Lacks full detail on output structure, error states, or edge cases. Adequate for a basic extraction 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?

All 7 parameters described in schema (100% coverage). Description mentions filtering/pagination but adds minimal extra meaning 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?

Clear verb 'Extract' with specific resource 'API call records from an APMX capture', mentions filtering, pagination, and record structure. Distinct from sibling tools like apmx_calls_around.

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 explicit when-to-use or alternatives. Implies usage for general extraction with filters, but does not differentiate from similar siblings like apmx_calls_around.

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 mentions 'wraps handle correlation with parameter decoding', which gives insight into internal processing. However, it does not explicitly state read-only behavior, error handling, or performance impacts. For a read-only analysis tool, this is adequate but not exceptional.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences that are front-loaded with the primary action and output, followed by a brief elaboration on the handling. No redundant or unnecessary information. 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 that the schema fully documents parameters and no output schema exists, the description adequately covers what the tool returns. It lists specific fields (target PID, process name, shellcode sizes, etc.) and explains the forensic-friendly nature. Missing details about error conditions or limitations, but overall complete for its 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 does not add meaning beyond the schema-provided parameter descriptions (file_path and process_index). Both parameters are already well-documented in the schema, so the description's added value is minimal.

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 extracts injection chain details from APMX captures and lists specific outputs (target PID, process name, shellcode sizes, etc.). It is specific about the resource and verb, but does not explicitly differentiate from sibling tools like apmx_calls_around or apmx_get_calls.

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 tool versus alternatives. The description implies it's for injection chain details but does not mention preconditions, exclusions, or comparisons with other apmx tools. Lack of context signals such as 'use if you need injection-specific data' leaves the agent without clear selection criteria.

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, but the description transparently describes a read-only parse operation without side effects. However, it doesn't explicitly state that it doesn't modify files or require special permissions, leaving minor ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first explains action and output, second provides usage guidance. No wasted words, front-loaded with key information.

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?

Tool has no output schema, but description compensates by listing return values. For a simple parse tool with one parameter, this is mostly complete, though additional details about file size limits or error handling would improve it.

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% for the single parameter, so the description adds no new semantic detail 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?

Description clearly states the tool parses Rohitab API Monitor capture files and lists the returned data (process info, modules, API call count). It distinguishes itself from sibling tools by implying it's the first step.

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 says 'Use this first to understand what's in a capture,' providing clear guidance on when to use this tool over siblings.

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; description fails to disclose performance characteristics, limitations, or error handling for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences without waste; directly states purpose and output format.

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?

Adequate for a search tool; covers input and output basics but lacks details on return structure or edge cases.

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 descriptions; description adds minor context about searching integer or string values and highlighting matches.

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?

Clear verb 'Search' with resource 'API calls by parameter value' and distinct from siblings like apmx_get_calls.

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?

Implied usage from purpose, but no explicit when-to-use or alternatives; could benefit from context like 'use instead of apmx_get_calls when filtering by parameter value'.

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 must fully disclose behavioral traits. It only states what the tool does (parse) but does not mention that it reads local SQLite files, that it is read-only, or any potential side effects. This is insufficient for an agent to understand the tool's 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 two sentences with no wasted words. The first sentence introduces the action and browsers, the second lists the questions answered, making it efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 8 parameters with clear schema descriptions, but no output schema is provided. The description does not explain what the return values look like or how results are structured, leaving a gap for the agent despite good schema coverage.

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 no additional meaning beyond the schema; it only reiterates the high-level purpose. The 'answers' part hints at output but does not directly explain parameters.

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 with a specific verb 'Parse' and identifies the resource 'browser history and downloads' from three named browsers. It also lists the specific questions it answers, making the purpose unambiguous and distinguishable from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives or when not to use it. It implies the user needs a history file path but does not clarify prerequisites or context, leaving the agent without clear usage boundaries.

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 must disclose behaviors. It mentions auto-detection of paths, sorting, and deduplication, but does not disclose potential limitations such as performance considerations, memory usage, or what happens when artifacts are missing. The description is adequate but lacks richness.

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 three sentences long, each providing essential information: what the tool does, the output characteristics, and the core question it answers. No redundant or unnecessary 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 the complexity (11 parameters, no output schema), the description covers the main purpose and sources adequately. It does not explain the return format or processing limits, but for basic use it is sufficient. Slightly incomplete for advanced scenarios.

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 significant meaning beyond what is already in the schema; it repeats the concept of auto-detection and override paths but provides no additional semantic context for parameters.

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 'build' and the resource 'forensic timeline', lists specific artifact sources (MFT, USN, etc.), and distinguishes from sibling tools that parse individual artifacts. It also describes the output characteristics (sorted, deduplicated) and the overarching question it answers ('What happened and when?').

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 this tool is for a unified chronological view, but it does not explicitly state when to use it versus alternatives (e.g., individual parsers like disk_parse_mft). There are no usage exclusions or explicit comparisons to sibling 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?

No annotations are provided, so the description must disclose behavioral traits. It states the tool parses a file and extracts evidence, but does not mention whether it is read-only, potential performance impact, required permissions, or error conditions. This is minimal transparency.

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: one sentence followed by a phrase. It is front-loaded with the action and contains no redundant 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 no output schema, the description should explain return structure. It mentions extracted data types but not format or ordering. Parameter descriptions in schema cover filters, so completeness is moderate.

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 clear descriptions for all 7 parameters. The description adds no additional parameter information beyond the schema, so 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 clearly states the tool parses Amcache.hve to extract program execution evidence including SHA1 hashes, file paths, and timestamps. It explicitly says 'Proves a file existed and was prepared for execution,' which differentiates it from siblings like disk_parse_mft or disk_parse_prefetch.

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 analyzing Amcache.hve but does not provide explicit guidance on when to use this tool versus siblings like disk_parse_mft, disk_parse_prefetch, or disk_parse_srum. No when-not-to-use or alternative recommendations.

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 must disclose behavioral traits. It correctly describes the tool as parsing and analyzing timestamps, implying it is read-only. However, it does not explicitly state that it does not modify data, require special permissions, or have rate limits, leaving some behavioral gaps.

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 (three sentences) and front-loaded with the core action. It efficiently conveys purpose, scope, and key features without extraneous detail, making it easy for an agent to parse.

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?

Despite no output schema, the description hints at return values (metadata, timestamps, ADS). It covers the tool's main capabilities and questions it answers. For a complex tool with 10 parameters, it provides sufficient context, though it could briefly mention output structure.

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?

Input schema covers all parameters (100% coverage), so the description's role is minimal. It adds context by tying parameters to the tool's purpose (e.g., timestomping detection), but does not enrich individual parameter descriptions 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?

The description clearly states the tool parses $MFT for file metadata, ADS, and timestomping detection, distinguishing it from sibling disk parsing tools (e.g., disk_parse_prefetch). It answers specific forensic questions, leaving no ambiguity about its function.

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 guides usage by highlighting timestomping detection and named stream analysis, which differentiates it from other disk parsers. It provides explicit answers to common forensic queries, helping an agent decide when to invoke this tool, but lacks explicit 'when not to use' or alternative tool references.

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 must disclose behavioral traits. It mentions pagination support and warns about large output with include_loaded_files, but lacks details on authorization requirements, error handling for invalid files, or whether the operation is read-only. Some behavioral context is present but incomplete.

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 three concise, front-loaded sentences. Every sentence adds value: the first states the core purpose, the second clarifies scope (file vs. directory), and the third mentions pagination. 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 no output schema, the description could better explain return values (e.g., fields in each parsed entry). It mentions high-level output (history, run counts, times) but lacks specifics. Pagination support is noted, but behavior for empty results or errors is omitted.

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 meaning beyond the schema: it explains that path can be a file or directory and that executable_filter applies only to directory parsing. However, this is not substantial additional insight.

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 parses Windows Prefetch files to determine program execution history, run counts, and last execution times. It specifies the resource (Prefetch files) and the action (parse), distinguishing it from sibling tools that handle other disk artifacts like MFT, SRUM, etc.

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 mentions parsing a single .pf file or entire Prefetch directory, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., disk_parse_amcache for application compatibility). No when-not-to-use or comparative guidance is given.

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 burden of behavioral disclosure. It adds useful caveats such as 'Resource counters are not interpreted as elapsed runtime' and mentions derived MB/MiB and optional network aggregation, but it does not state read-only behavior, output format, or potential side effects/requirements.

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 three concise sentences, front-loaded with the core purpose. Each sentence adds non-redundant information: what is parsed, supported capabilities, and an important interpretive caveat.

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 provides a high-level summary of the output categories and caveats, which is helpful given there is no output schema. It is adequate for an 8-parameter tool with fully documented schema parameters, though it stops short of describing response structure or row-level details.

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 mentions application/time filters, derived units, and network aggregation, but these are already documented in the input schema and it adds little semantic value beyond what the schema 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?

The description uses a specific verb ('Parse') and resource ('SRUDB.dat'), and clearly states what data it extracts: raw application resource counters and network bytes sent/received. This distinguishes it from sibling disk_parse_* tools by naming the exact artifact it targets.

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 through its focus on SRUDB.dat, but it does not explicitly state when to use this tool over siblings or provide exclusions. There are no alternative-tool references or when-not-to-use guidance, leaving usage to be inferred.

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 must stand alone. It implies a read-only operation (parsing), but does not explicitly state non-destructive behavior, required permissions, or any side effects. It adds moderate context about the kind of information returned.

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 very concise (two sentences, ~40 words), front-loading the purpose and key questions answered. No extraneous information.

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 10 parameters and no annotations or output schema, the description covers the primary purpose but does not explain output modes, filtering nuances, or how parameters interact. Adequate for a simple parse tool but could be more 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?

Input schema has 100% description coverage, with detailed descriptions for each parameter. The tool description does not add additional meaning beyond the schema, so baseline score of 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?

Description clearly identifies the tool as parsing the USN Journal for file system change history, with specific operations (create, delete, modify, rename). It distinguishes itself from sibling disk_parse_* tools by the target artifact ($J file).

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 explicit guidance on when to use this tool versus alternatives like disk_parse_mft. The description states what questions it answers but does not compare or contrast with other tools, leaving the agent to infer usage 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?

No annotations are provided, so the description carries full burden. It discloses the output format (TSV), behavior (returns one line per event with attack-relevant columns), and event type details. It does not explicitly state read-only, but the nature implies it.

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 relatively concise and front-loaded with the purpose. It includes necessary details about event types and columns, though it could be slightly more streamlined.

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 5 parameters, no output schema, and no annotations, the description covers the main aspects: purpose, output format, event types, and filtering. It is mostly complete for rapid triage 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 60% (descriptions for 3 of 5 params). The description adds value by explaining the output format and columns for each event type, which helps agents understand parameter usage 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 explicitly states it is a 'Compact TSV summary of security events for rapid triage' and lists specific event types and columns. This clearly distinguishes it from sibling tools like evtx_search or evtx_security_search by focusing on attack-relevant summaries.

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 stating it is for rapid triage and can fit entire attack chains in a single call. It implies when to use it (quick summary) but does not explicitly state when not to use it or mention 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?

With no annotations, the description carries the full behavioral burden and does add useful context: the seven-day window cap, retained row fields, and an identity caveat. However, it omits read-only status, permissions, pagination behavior, and how max_scan capping affects result completeness.

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 compact sentences front-load the core purpose and append a relevant caveat. There is no filler, though the second sentence mixes result-shape information with an interpretive warning.

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 an 11-parameter forensic correlation tool with no annotations and low schema description coverage, the description is under-specified. An output schema may cover return values, but the description still leaves major usage and parameter-semantics 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 only 36%, so the description should compensate, but it only implies the logon_id and start/end time parameters. It leaves computer, event_ids, cursor, offset, limit, max_scan, and max_chars unexplained beyond sparse 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?

States a specific verb ('Find') and resource ('subject/target occurrences of one logon ID') within an explicit time window. It distinguishes itself from broad sibling searches by centering on logon-ID correlation, though it does not name alternative tools.

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 when-to-use or when-not-to-use guidance. The note that matching IDs alone do not establish identity is an interpretive caveat, not routing advice or a comparison to sibling tools such as evtx_search or evtx_security_search.

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 must carry full behavioral burden. It adds useful context: preserving provenance and not inventing missing SIDs, reporting placeholders like 'Malformed Security Descriptor.' However, it does not clarify whether this is a read-only operation, what permissions are required, or what the output looks like beyond what the output schema provides.

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 tightly written sentences with no wasted words. The core purpose is front-loaded, and the second sentence efficiently adds a key behavioral guarantee about provenance and missing SIDs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with six parameters, three required, and only 50% schema description coverage, the description is too sparse. It does not compensate for undocumented parameters, lacks usage guidance, and provides minimal behavioral context. The presence of an output schema covers return values, but overall completeness is low.

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 only 50% (encoding, max_aces, and max_chars have descriptions; field, event_ref, and evtx_path do not). The description does not mention any parameters or add meaning beyond the schema, leaving three parameters undocumented in both schema and description.

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 a specific verb and resource: 'Describe a security-descriptor value in a source-bound EVTX event.' It distinguishes itself from generic EVTX tools by scoping to security descriptors and emphasizing provenance. However, it does not explicitly differentiate from the sibling tool 'security_descriptor_decode', so it falls short of a 5.

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 tool versus alternatives like 'security_descriptor_decode' or other EVTX tools. The description implies it is for describing security descriptors in EVTX events, but there are no explicit conditions, exclusions, or prerequisites.

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. The description merely says 'Get description', which implies a read operation, but it does not disclose any behavioral traits such as required permissions, error behavior for invalid event IDs, or the role of the channel parameter. The description carries a heavy burden without annotations and fails to provide sufficient 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 extremely short (a single phrase), but it is under-specified rather than concise. It does not provide enough information to effectively use the tool, leaving the agent with minimal 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 has two parameters and no output schema, the description is too minimal. It does not explain the return format, error handling, or the significance of the 'channel' parameter, making it incomplete for an agent to invoke correctly.

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 0%, so the description must compensate for the lack of parameter documentation. However, it does not mention the 'event_id' (integer) or 'channel' (string, default 'Security') parameters at all, offering no guidance on their meaning or usage.

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 'Get description of a Windows Event ID', which is a specific verb-resource pair and provides a clear purpose. It does not differentiate from siblings like evtx_search or evtx_get_stats, but it is distinct enough in function.

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 tool versus alternatives such as evtx_search or evtx_attack_summary. There are no when-to-use, when-not-to-use, or prerequisite instructions, leaving the agent without context for selection.

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 and does add real behavioral facts: a unique file, a SHA-256 digest, and the crucial distinction that preview clipping does not discard file rows while scan/row caps mark the export incomplete. It still omits error/failure behavior, permission expectations, and what 'unique 0600, no overwrite' (only in the schema) implies operationally.

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 tight sentences with the primary action front-loaded and no filler. The density is near the edge of cryptic, but each clause (SHA-256, bounded preview, cap vs clip semantics) carries distinct information.

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 return values needn't be explained, and the export/artifact semantics are covered. For an 18-parameter tool with a nested where object and heavy time-range filtering, the description still leaves filtering and predicate behavior to the schema alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 44% across 18 parameters, so the description should compensate more than it does. It clarifies the interplay of scan/row caps and the preview budget, but leaves the filter surface (contains, not_contains, event_ids, provider, start_time/end_time, where) without additional meaning beyond what the schema already says.

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 (persist/export) and resource (selected EVTX matches) plus the artifact produced (a unique JSONL file with SHA-256 and a bounded preview). The word 'persist' implicitly distinguishes it from evtx_search-style read-only siblings, though no sibling is named explicitly.

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 statement of when to prefer this over evtx_search, evtx_security_search, or evtx_get_event, nor any prerequisites. The phrase 'all selected matches' hints the tool consumes filters established elsewhere, but the agent gets no explicit routing 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?

No annotations are provided, so the description carries the full burden. It discloses one meaningful behavioral trait – that evidence fields are never shortened – but says nothing about permissions, side effects, or how max_chars interacts with that guarantee, leaving the safety/behavior profile largely undeclared.

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 tight sentences, front-loaded with the action and the key prerequisite, then the truncation guarantee. No 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?

An output schema exists, so return-value explanation is unnecessary, and the description covers the core identity and the event_ref provenance. The main gap is the unexplained relationship between max_chars and the 'never shortens' guarantee, plus no mention of what evtx_path must point to.

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 0%, so the description must compensate. It adds meaning for event_ref (source-bound, produced by evtx_search) but says nothing about evtx_path or max_chars, and the 'never shortens evidence fields' claim only obliquely gestures at max_chars 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?

States a specific verb (retrieve) and resource (full normalized event) and distinguishes itself from siblings by naming evtx_search as the producer of the required event_ref. An agent can tell this is the detail-fetch counterpart to a search tool without reading any 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?

It explicitly ties usage to a source-bound event_ref originating from evtx_search, giving clear context for when this tool applies. There is no explicit when-not guidance or exclusion, but the prerequisite is unambiguous.

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 burden. It states 'Get statistics' implying a read operation, but does not mention non-destructive nature, auth needs, or any other 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?

The description is a single sentence that conveys the core purpose and output details without extraneous information.

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 a single parameter and no output schema, the description adequately describes the output types (event counts, time range, Event ID distribution). Some might consider it slightly incomplete regarding the exact format, but it is suitable for a simple statistical 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 coverage is 100% (evtx_path has a description). The description adds no additional parameter details beyond what the schema 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?

The description clearly states it gets statistics (event counts, time range, Event ID distribution) from an EVTX file. This distinguishes it from sibling tools like evtx_search or evtx_explain_event_id.

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 use when overall statistics are needed, but does not explicitly state when to use this versus other EVTX tools or when not to use it.

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; the description only says 'list files' without disclosing error handling, file filtering behavior, or performance implications.

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, concise but too brief to provide necessary details; it's not overlong but lacks substance.

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, no annotations, and only partial param descriptions, the description should explain return format, sorting, or filtering; it does not.

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 50% (only 'directory' has description); the tool description adds no extra meaning beyond what's in the schema, failing to compensate for the missing 'recursive' description.

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 action (list) and resource (EVTX files in a directory), and it distinguishes from siblings like evtx_search and evtx_attack_summary by specifying file listing.

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 tool versus alternatives (e.g., evtx_search), no when-not-to-use conditions, and no prerequisites mentioned.

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 and does disclose meaningful traits: counts/timestamps/event references are preserved, distributions are bounded, unknown statuses are reported honestly, and rarity is explicitly stated not to be an attack verdict. It still omits read-only/permission and performance characteristics, but the output-semantics disclosure is solid.

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 dense, front-loaded sentence that leads with the action and resource and then layers the differentiating behaviors. No filler or repetition, though the phrasing is compressed enough that some clauses need unpacking.

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 return-value explanation is not required, and the mutation/permission profile is trivially read-only. However, for a 19-parameter tool with thin schema documentation, the description leaves filtering and pagination semantics unexplained, which an agent needs in order to call it correctly.

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 only 26% across 19 parameters, so the description must compensate. It does explain the core semantics behind order (rare-first), aggregate, and bounded distributions, but says nothing about the many filter parameters (domain, username, process, client_ip, status, event_ids) or the cursor/offset paging contract.

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 (summarize) and resource (NTLM Operational events 4021/4022/4023), plus the distinctive behavior of aggregating repeated shapes and ordering rare combinations first. It does not name a sibling tool to differentiate from (e.g. evtx_attack_summary or evtx_get_stats), but the scope is specific enough to identify the tool.

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?

Usage is implied by the tool's specialty (NTLM operational event triage with rarity ordering), and the default order=rare_first is surfaced, but there is no explicit 'use this instead of X when Y' guidance despite many overlapping evtx_* siblings such as evtx_search and evtx_attack_summary.

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 does add real behavioral context — result-order preservation, source-bound cursors, and projection/budget semantics — which is more than most. However it says nothing about read-only safety, error behavior, or the cost/cap behavior beyond the passing mention of budgets.

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 tightly packed sentences, front-loaded with purpose before capabilities. Efficient, though the second sentence is a dense feature list that would benefit from slightly more specificity about what 'whole-record budgets' implies.

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 an 18-parameter, nested-object search tool with no output schema and no annotations, the description covers core behaviors but leaves combination rules (cursor vs offset is only in the schema), required-path semantics, and result-shape expectations to other sources — adequate but not 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 coverage is 50% on 18 parameters, so the description must compensate. It does group the filter params (time/event-id/keywords/provider) and names the projection/budget/cursor concepts, but ignores limit, offset, where, timestamp_precision, and where_case_sensitive, which remain undocumented in both places.

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 ('Search') and resource ('EVTX events') plus the four filter dimensions (time, Event ID, keywords, provider). An agent can tell what it does, but the description never distinguishes it from siblings like evtx_security_search or evtx_get_event, which overlap heavily on the same EVTX 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?

No when-to-use guidance, prerequisites, or alternatives are given. With 7+ sibling evtx_* tools, the agent is left to infer from the name alone whether this is the general-purpose search versus evtx_security_search or evtx_get_event.

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 that output uses compact fields, a response budget, and cursor-based continuation, which is useful behavioral context, but it says nothing about read-only semantics, result shape, or how capping/inexact totals behave (left to 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?

A single front-loaded sentence that names the resource and the inherited behavior with no filler. Nothing redundant or 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?

For a 13-parameter tool with a nested where object, heavy enums, and no output schema, the description is very thin. It defers almost everything to evtx_search, which the agent may not know, and provides no return-value or paging 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 62%, so many parameters already carry their own descriptions. The phrase 'compact fields, response budgets, and continuation controls' loosely maps to compact/max_chars/cursor, but the description adds no operational detail for the 13 parameters and leaves the nested where object 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 ('Search') plus resource ('Security events') and a scoping mechanism ('by named type'), which is enough to tell it apart from evtx_search. It stops short of fully disambiguating what evtx_search returns that this one does not, but the purpose is concrete.

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 a division of labor with evtx_search (named event types vs. general search) and inheritance of its controls, but never states when to prefer this tool or when-not. Usage is inference-based rather than explicit.

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 present, so the description carries the disclosure burden. It explicitly says 'static analysis', signaling a read-only operation, and lists the extracted data (headers, imports, exports, hashes, Authenticode metadata, suspicious indicators). It does not mention performance caveats or limitations, but the static nature and output scope are well disclosed.

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, front-loaded sentence that states the core action and then lists the extracted artifacts in a compressed sequence. Every element adds information, with no 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?

The definition covers the input type, the analysis action, and the output categories, while the schema fully documents all five parameters and defaults. Without an output schema, the enumerated extraction list gives the agent a good picture of the return content; no critical missing context for invoking 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?

Since schema_description_coverage is 100%, baseline is 3. The description adds no parameter-level semantics beyond the schema; it mentions output categories but not how they map to the detail_level, extract_strings, calculate_hashes, or check_signatures parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Perform static analysis') and a concrete resource ('Windows PE files (EXE/DLL/SYS)'), then enumerates the output categories. This clearly distinguishes it from sibling forensic tools focused on EVTX, registry, or disk artifacts.

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 clearly establishes the file type this tool applies to, so an agent can select it for PE files. However, it does not mention alternatives or conditions where another tool (e.g., api_analyze_imports for import-focused analysis) would be preferable.

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 burden. It states the tool lists event IDs, which implies a read operation. However, it does not specify the format of the output, whether the list is exhaustive or curated, or any side effects. For a simple listing tool, the description is minimally 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 a single, front-loaded sentence with no filler. Every word contributes to stating the tool's 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 the tool's simplicity (one required enum parameter, no output schema), the description is adequate but minimal. It does not explain what 'important' means, how the IDs are determined, or what the output looks like. For a tool that likely returns a list of integers, more context would help an agent gauge its utility.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not mention the 'channel' parameter or its enum values. The input schema fully defines the parameter with an enum, but the description adds no additional meaning, such as examples or context for what 'important' means per channel. Schema description coverage is 0%, so the description should compensate but does not.

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 action ('List') and the resource ('important Event IDs for a log channel'). It distinguishes from siblings like evtx_explain_event_id which explains a single event ID, and evtx_search which searches events, by focusing on listing important predefined IDs for a given channel.

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 guidance on when to use this tool versus alternatives. It does not mention specific use cases, prerequisites, or under what conditions this tool is preferred over siblings like evtx_explain_event_id or evtx_get_stats.

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 must disclose behavioral traits. It only says 'List' (implying read-only) but does not clarify whether it accesses a live system or forensic image, permission requirements, or output format (e.g., key paths, timestamps, values).

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 very short (one sentence) but omits essential details about the parameter and output. While front-loaded and efficient, it sacrifices completeness for brevity.

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 must explain what is returned (e.g., list of key paths or full key details). It does not. The category parameter is also unexplained. For a single-parameter tool, this is inadequate.

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 has 0% description coverage for the category parameter, and the tool description does not mention it or explain what each enum value returns. The agent only sees the enum labels, which lack semantic clarity beyond their names.

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 'List forensically important registry keys' indicates a verb and resource but fails to define what qualifies as 'important' or what the output contains (e.g., key names, paths, values). It does not mention the category parameter, leaving scope ambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus sibling tools like registry_get_network, registry_get_persistence, or registry_search. The agent is left to infer the use case without any contextual hints.

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 must fully disclose behavior. It mentions searching multiple artifacts, auto-detection of paths, and optional YARA scanning, but does not state if the tool is read-only, its performance impact, or any side effects. The description gives moderate behavioral insight but leaves gaps.

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 three sentences: purpose, artifacts covered, and example questions. It is front-loaded and efficient, but could be more structured by separating parameter hints. Still, it is concise and easy to parse.

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 (12 parameters, 2 required, no output schema), the description provides a good overview but lacks details on output format, error handling, or behavior when artifacts are missing. It answers conceptual questions but leaves implementation details unspecified.

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 documents all parameters. The description adds context by listing the artifact types searched, which aligns with the override path parameters, but does not add significant meaning beyond the schema. Baseline score of 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 clearly states the tool hunts for IOCs (hash, filename, IP, domain) across multiple forensic artifacts, listing specific ones (Prefetch, Amcache, etc.). It distinguishes from sibling tools that parse single artifacts (e.g., disk_parse_mft) by offering a comprehensive search. The purpose is specific and actionable.

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 includes example questions that indicate when to use the tool (e.g., 'Where does this IOC appear?'). It implies it is for cross-artifact hunting, but does not explicitly state when not to use it or mention alternative tools for single-artifact analysis. Guidance is clear but lacks exclusion criteria.

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 must disclose behavioral traits. It indicates scanning of various data sources but does not mention side effects, authorization needs, or whether the operation is read-only. Critical behavioral context is missing.

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 exceptionally concise: two sentences front-load the core purpose and a key example. Every word adds value with no 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 tool's complexity (8 parameters) and no output schema, the description covers the main purpose and sources adequately. However, it lacks guidance on workflow, prerequisites, or return format, leaving minor 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 coverage is 100% with each parameter described. The description adds the bundled pack name as an example, but does not significantly augment meaning beyond the schema. Baseline score of 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 clearly states the verb 'Hunt', the resource 'behavioral IoCs from a metadata pack', and the scope across multiple artifact types (logs, texts, filenames, PCAPs). It distinguishes from sibling 'hunt_ioc' by specifying the bundled pack mechanism.

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 pack-based hunting but does not explicitly state when to use this tool versus alternatives (e.g., hunt_ioc) or when not to use it. No exclusions or prerequisites are mentioned.

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 must disclose behavioral traits. It mentions auto-detection of CSV type but does not describe whether the tool is read-only, what side effects occur (e.g., file persistence), or the response format. With a score of 3, it provides basic context but lacks depth.

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, consisting of two sentences that front-load the core action ('Import pre-parsed CSV...') and 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?

The tool has no output schema, so the description should hint at return values. It only says 'for querying,' which is vague. Filtering behavior is implied by parameters but not explained. More detail on what the tool returns would improve completeness.

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 input schema already describes each parameter. The description adds marginal value by noting auto-detection, but this is already reflected in the 'auto' default for csv_type. Thus, a baseline score of 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 clearly states the tool imports pre-parsed CSV from Eric Zimmerman tools for querying, which differentiates it from sibling tools that parse raw data (e.g., disk_parse_mft). The verb 'import' and specific resource 'pre-parsed CSV from EZ tools' make the purpose 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 says 'Useful when you already have parsed output from EZ tools,' which implies when to use this tool. It does not explicitly mention when not to use it or suggest alternatives, but the context of sibling tools provides some differentiation, earning 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?

No annotations are provided, so the description carries full burden. It discloses the tool correlates multiple artifacts and provides answers, but does not mention limitations such as handling of missing artifacts, performance implications, or required privileges. The parameter description notes auto-detection of paths, adding some transparency.

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, using multiple short sentences that each add value: it states the tool is comprehensive, specifies correlated artifacts, answers key questions, and mentions outputs (confidence scoring, timeline). No filler or 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 complexity (7 params, no output schema, no annotations), the description covers the main purpose, artifacts, and questions. It lacks details on output format or behavior when artifacts are missing, but is reasonably complete for a tool with strong schema descriptions.

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 baseline is 3. The description adds no additional semantics beyond the schema descriptions; it focuses on overall purpose. Parameters are well-documented in the schema, so no further elaboration needed.

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: comprehensive execution analysis by correlating Prefetch, Amcache, and SRUM. It answers specific questions (whether executed, when, duration) and provides unified timeline and confidence scoring. This distinguishes it from sibling tools that parse individual artifacts.

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 execution investigation but does not explicitly state when to use this tool versus alternatives like disk_parse_prefetch or evtx_search. No when-not or alternatives are given, leaving some 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?

The description discloses that it correlates multiple sources and can override auto-detected paths, but lacks behavioral context such as whether artifacts must be present, performance impacts, or destructive actions. With no annotations, more detail would be beneficial.

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 (three sentences) and front-loaded with the main purpose, followed by sources and questions. No unnecessary 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 11 parameters and no output schema, the description does not explain the output format, how correlation results are presented, or potential limitations. This leaves agents without full context for invoking 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?

Schema coverage is 100%, so baseline is 3. The description does not add extra meaning to parameters beyond what the schema already provides, only summarizing the overall purpose.

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 a comprehensive investigation correlating multiple artifact types (Browser History, ShellBags, LNK files, RecentDocs) to answer specific questions about user activity. It distinguishes itself from sibling tools like browser_get_history or user_parse_shellbags by combining them.

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 that this tool is for comprehensive investigation, while siblings cover individual sources. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites.

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 full burden for behavioral transparency. It mentions output (license metadata, rule counts) but does not disclose whether the operation is read-only, idempotent, or has any side effects or authorization requirements.

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 sentence of 18 words. It is front-loaded with the action and resource, and every phrase adds value. No unnecessary 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?

The description covers the basic purpose and output fields (license metadata, rule counts) but does not specify the return format, whether filtering is possible, or if the list includes built-in packs. Given no output schema and multiple siblings, more detail on the output structure would improve completeness.

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 optional parameter 'extra_paths' with its own description. The tool description does not add any additional meaning beyond what the schema already provides. Since schema coverage is 100%, baseline score of 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 clearly states the tool lists bundled and optional external behavioral IoC packs with license metadata and rule counts. It uses specific verb 'list' and resource 'IoC packs', differentiating from sibling tools like 'hunt_ioc_pack' which hunts rather than lists.

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 listing packs but provides no explicit guidance on when to use this tool versus alternatives like hunt_ioc_pack. No when-not-to-use or prerequisite information is given.

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 behavioral burden and does add meaningful non-obvious context: evidence-backed forest-root identification, retained uncertainty in local-domain attribution, and explicit refusal to guess SID prefixes or extract credentials. It still does not state read-only safety or performance characteristics, but the disclosed limitations are valuable.

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 dense sentences, front-loaded with purpose and followed by caveats. It avoids repetition and wasted words, though the technical phrasing is somewhat compressed.

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 return values need not be described. However, for a five-parameter tool with no annotations and only 40% schema coverage, the description leaves usage selection and parameter meaning largely unexplained.

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 only 40%, so the description should compensate but does not mention any parameter semantics. Terms like max_scan, max_chars, diagnostic_limit, and domain_dn are left entirely to the schema, and the required ntds_path is undocumented.

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 gives a specific verb and resource: read domain metadata and forest-root identification from offline NTDS. It is clear enough to distinguish from object lookup tools, though it does not explicitly name sibling alternatives such as ntds_get_trusts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not state when to use this tool versus alternatives or what prerequisites exist. It implies a domain-metadata read from an offline NTDS file, but offers no explicit selection 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, the description carries the safety profile: read-only metadata, allowlisted fields, no credential decryption, and no SYSTEM requirement. It also discloses edge-case behavior for deleted/recycled and duplicate matches. It does not cover permissions, scan limits, or error behavior 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?

Three compact sentences with the core operation and constraints front-loaded. No filler; each clause carries purpose, edge case, or safety information.

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?

Output schema exists so return values need not be explained, and the description adequately covers purpose and safety. However, for a 7-parameter tool with incomplete schema descriptions, it leaves several parameters and memory/scan-limit semantics unexplained.

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 has only 57% description coverage across 7 parameters. The description adds no syntax or meaning beyond the schema's own SAM selector and allowlist notes, and it says nothing about ntds_path, domain_dn, max_chars, diagnostic_limit, or max_scan limits.

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 'Read', resource 'allowlisted offline NTDS metadata', and exact selector 'one exact SAM name'. The SAM-name scope implicitly distinguishes it from sibling ntds_get_object_sid and other NTDS tools.

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?

Clearly implies use for exact SAM lookups and not for wildcard/list modes, and describes duplicate/deleted handling. Does not name an alternative when a SID lookup is needed, so it stops short of full when/when-not 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, the description carries the full behavioral burden and discloses meaningful traits: it reports not-found, ambiguity, and incomplete evidence explicitly, and never selects an arbitrary duplicate. It does not state permissions, read-only status, or performance characteristics, but the ambiguity and duplicate-handling behavior is unusually well specified.

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 tightly written sentences with no wasted words. The main purpose is front-loaded, followed immediately by the key behavioral guarantee about ambiguity and duplicates.

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 return values need not be explained. However, for a six-parameter forensic tool with only partial schema coverage, the description omits important input semantics and prerequisites around the offline NTDS path and scan limits, leaving the definition 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 only 50%, and the description does not compensate for undocumented parameters such as max_chars, diagnostic_limit, and ntds_path. It reinforces the exact SAM selector requirement, but that is already in the schema, and other parameters like max_scan and domain_dn are left 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?

The description states a clear verb and resource: resolve an exact SAM selector to offline NTDS SID metadata. It is specific enough to distinguish the operation from generic object lookup, but it does not explicitly differentiate itself from the sibling tool ntds_get_object_by_sam.

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?

Usage is implied: use this tool for exact SAM selector resolution to SID metadata. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling is named for cases where object lookup rather than SID resolution is wanted.

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