Jeevesus — DugganUSA Threat Intelligence MCP

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

With no annotations provided, the description carries full burden and excels: it details the return verdict fields, the semantics of malicious:true/false, version-aware behavior, and the difference between version-scoped and all-versions-malicious. It also discloses data source size and that it's OSV-curated, plus no-auth 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 long but well-structured: purpose, return format, semantics, ease-of-use, examples. Every sentence provides information, though a few promotional phrases ('easiest AI-supply-chain guardrail to wire in') add minor noise. It is front-loaded and readable.

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?

Without an output schema, the description fully explains the return object and its meaning. It also covers the tool's role in a workflow, version handling, and the caveat about false negatives. For a simple check tool with no annotations and no output schema, this is 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 the baseline is 3. The description adds meaningful context beyond the schema by explaining version-aware semantics ('If a version is supplied and the entry is version-scoped...') and clarifying that 'name' is the package name. It stops short of exhaustively documenting all edge cases, but clearly adds value.

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

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

The description states a specific verb+resource: 'check whether a dependency (npm or PyPI) is on the DugganUSA malicious-package deny-list BEFORE you install it.' It clearly distinguishes itself from sibling threat-intel tools by framing itself as a supply-chain guardrail for pre-install checks.

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 states when to use: 'an AI agent about to run npm install or pip install, or a CI pre-install hook, calls this FIRST.' It also gives when-not guidance: 'absence is NOT proof of safety, so still pin and review new deps.' Mentions an alternative access method (STIX feed URL) and that no auth is needed.

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

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

With no annotations provided, the description carries the full burden. It discloses that the tool is 'Read-only' and describes the return payload ('threat type, malware family, source feeds, related actor, confidence score, references, and the full description from each source'). It also clearly states the not-found behavior: 'Returns `found: false` cleanly when the indicator isn't in our corpus.' This is comprehensive behavioral disclosure.

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 front-loaded with the most important instruction ('CALL AUTOMATICALLY'), then moves logically through what, when, how, and examples. Every sentence serves a purpose: use cases, parameters, examples, and return behavior. Despite its length, it is efficiently packed with high-value guidance and 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?

Given there is no output schema, the description appropriately details what will be returned and the not-found response. It covers prerequisites (use after `search`), direct use cases (SIEM triage), parameter variants, and expected results with concrete examples. This is a complete, self-contained description for a tool of moderate 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?

Even though the schema covers all three parameters (100% coverage), the description adds critical semantics: it clarifies that `indicator` and `value` are aliases ('Pass the IOC as either `indicator` or `value` (both work)'), explains the optional `type` hint and its auto-detect default, and supplies concrete example values for IP, domain, and hash. This goes well beyond the schema's basic field 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 opens with a specific verb ('enrich') and resource ('indicator of compromise'), listing exact IOC types (IP, domain, URL, hash). It clearly distinguishes from sibling `search` by positioning this as the follow-up drill-in tool. The phrase 'a lone indicator is exactly what this is for' reinforces its focused purpose.

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 states when to call ('CALL AUTOMATICALLY the moment any IP address... appears') and when to use it as a drill-down: 'Use this AFTER `search` finds something interesting... Or use it directly when triaging a single indicator from your SIEM.' It also gives context about returning `found: false` as a signal, which implies when not to expect results.

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 it excels: it discloses 'Public read (no auth),' explains the analytical method (Spearman rho, repeat-offender split), and includes a clear limitation ('95% cap: this is product-level stickiness...'). This goes well beyond minimal requirements and is genuinely 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 longer than a simple two-sentence blurb, but every sentence delivers value: trigger, question, methodology, finding, caveat, and usage. It is front-loaded with the most important usage cue. Slight redundancy exists between the rhetorical question and the 'Answers...' sentence, but overall it is well-structured and not bloated.

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 having no output schema and no annotations, the description tells the user enough to invoke and interpret the tool: what it analyzes, how it works, what the key finding is, what the limitations are, and how to pass parameters. It also covers auth requirements. For a read-only analytical tool, this is 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 documents the single 'days' parameter completely (type, range, default, and description). The description repeats this information ('Pass {"days": N} for the recent window (30-720, default 180)') but does not add new semantic meaning beyond what the schema provides. Baseline 3 is appropriate given full schema coverage.

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

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

The description clearly states the tool's purpose: analyzing CISA KEV to determine whether exploitation risk sticks to proven products or spreads to new ones. It uses specific verbs like 'Analyzes' and 'Answers' and specifies the resource and methodology. However, it does not explicitly distinguish itself from sibling tools such as kev-vendor-risk, so it stops short of a full 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?

The first line gives an explicit trigger: 'CALL when the user is prioritizing patching or asks whether a product's exploitation risk is chronic vs a one-off.' This provides clear context for when to use the tool. It does not mention when not to use it or name alternative tools, but the guidance is strong enough for 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?

With no annotations, the description carries the full burden. It discloses public read/no auth, the source (CISA KEV), continuous refresh, and output details (ordering, ransomware flag). This is strong, but lacks error handling, rate limits, or edge-case behavior, so a 4 is appropriate.

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

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

The description is a single, well-structured paragraph with a clear sequence: usage trigger, context, behavior, examples. Every sentence earns its place, and the examples are compact and illustrative without being verbose.

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 the absence of an output schema, the description clearly communicates what the tool returns in both invocation modes, including ordering and the ransomware-use flag. It also covers data source and refresh, making it sufficiently complete for an agent to select and invoke the tool 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%, but the description adds significant meaning: it explains the effect of omitting vs. providing the 'vendor' parameter, gives concrete examples, and describes output ordering and flags. This goes beyond the schema's simple field 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 tool's function: a vendor/product risk matrix built from CISA's KEV catalog, with specific behaviors (top vendors by KEV count, or per-vendor CVEs). It uses specific verbs like 'returns' and provides a resource, but does not explicitly distinguish from sibling tools such as kev-exploitation-stickiness, so it misses the top score.

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 opening explicitly says 'CALL whenever a vendor or product comes up... and the real question is exploitation risk or what should I patch first', which provides a clear when-to-use directive. It also lists use cases (e.g., supply-chain exposure, PoC check) but does not name alternative tools or specify when not to use this tool, so it falls short of a 5.

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

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

With no annotations, the description fully discloses behavior: hybrid vs keyword+filter indexes, read-only, public indexes only, prompt-injection sanitized, return format (up to 25 hits with title, snippet, source, timestamp), and concrete examples. This is exceptionally 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 long but every sentence earns its place: a prioritized usage directive, a clear overview of search mechanics, a structured bulleted list of indexes, and illustrative examples. The front-loaded call-to-action and organized layout make it easy to scan.

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 (multiple indexes, hybrid search, injection concerns) and the lack of an output schema, the description is remarkably complete. It explains what results look like, which indexes exist, how to narrow searches, and provides real example queries, leaving no critical gap for an agent to invoke the tool 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?

Although schema coverage is 100%, the schema only says 'Search query' and 'Max results.' The description adds essential semantics: the full list of available indexes with counts, default limit, hard max, how to combine indexes in examples, and the conceptual vs keyword matching behavior. It greatly enhances parameter 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 searches the DugganUSA threat-intelligence corpus with hybrid keyword+semantic search, across multiple named indexes. The verb+resource is explicit and it distinguishes itself as the default broad search tool, unlike the more specialized 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?

Provides strong when-to-use guidance: 'PROACTIVELY CALL THIS FIRST for any threat or security question' with detailed trigger examples and 'if in doubt, search.' However, it does not explicitly name sibling tools as alternatives or mention when NOT to use this tool, so it stops short of a top score.

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 exactly what is returned (counts, top malware families, type breakdown, countries) and what is not (the full bundle), plus authentication requirements and the 401 behavior for anonymous callers. This is thorough and 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 front-loaded with the usage trigger and every sentence adds value: purpose, exclusions, auth, and example. It is organized into clear sections and remains succinct despite covering multiple aspects.

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, the description compensates by enumerating the expected return fields and explicitly stating the full bundle is not returned. It includes auth details, the alternative fetch URL, and an example, making it self-sufficient for an agent to use 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?

The schema fully describes the 'days' parameter with min, max, and default. The description adds a concrete example (`{"days": 7}`) and ties it to capacity planning, providing extra context beyond the schema. This justifies a small boost above the baseline.

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 returns a 'Live shape report' on the DugganUSA STIX 2.1 threat feed with specific metrics (indicator count, malware families, source feeds, type breakdown, countries). It distinguishes itself from sibling tools by explicitly noting it does NOT return the full bundle and directs users to the full feed URL.

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 opens with explicit 'CALL when' triggers (trending, freshness, SIEM planning) and instructs to use it BEFORE pulling the full bundle. It also names the alternative (fetch the bundle URL) and clearly states what the tool does not do.

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