A read-only verified record of agent-operable GTM tools: search, fetch, compare, track changes.
Scored across 4 tools
Each tool targets a distinct operation: searching, retrieving a single record, comparing two records, and listing detected changes. There is no meaningful overlap between their inputs or outputs.
All four tools use consistent snake_case verb_noun naming: compare_tools, get_tool, list_changes, search_tools. The pattern is predictable and easy to infer despite minor singular/plural object choices.
Four tools is well-scoped for a read-only directory server: search, detail, compare, and change history cover the core workflows without redundancy. Each tool earns its place.
The surface covers all necessary read operations for the GTM-tools directory: discovery, retrieval, comparison, and change monitoring. Write operations are not expected for a curated external dataset, so there are no dead ends.
Compare two GTM tools head-to-head. Returns both full records plus a per-axis diff (overall score, API quality, GTM relevance, curation score, ease of use, free tier) naming the winning slug or 'tie'.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First tool (name or slug). | |
| b | Yes | Second tool (name or slug). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. Beyond that, the description adds valuable behavioral details about the return value, including the per-axis diff axes and the win/tie format, which the annotations do not convey. This enriches the agent's understanding of what to expect.
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 one dense sentence that leads with the core purpose and then lists the essential output details. There is no redundant wording; every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and no output schema, but the description sufficiently covers purpose, output composition, and the meaning of the result ('winning slug or tie'). It gives the agent all needed context for a comparison tool without over-explaining.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full descriptions for both parameters ('First tool (name or slug)' and 'Second tool (name or slug)'), so schema coverage is 100%. The description adds no additional parameter-specific meaning, matching the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Compare') and the resource ('two GTM tools'), and the phrase 'head-to-head' distinguishes this from sibling tools like get_tool, search_tools, and list_changes. It is specific and immediately understandable.
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 intended use case (comparing tools side-by-side) and explains what the output includes, giving clear context. However, it does not explicitly mention when to prefer this over alternatives or when not to use it, so it falls short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get one GTM tool by name or slug, with verified status (real last_checked_at), curation, product signals, adoption, and verified review themes.
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_slug | Yes | Tool name or slug, e.g. 'Apollo.io' or 'apolloio'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds substantive context about the return content (verified status, curation, product signals, adoption, review themes), which is valuable since no output schema is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core action and key data points. There is no redundancy or filler; every element contributes to understanding the tool.
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 single-parameter read tool with strong annotations and a fully described schema, the description is complete. It lists the key return aspects, making the tool's behavior predictable despite lacking an output schema.
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 the parameter 'name_or_slug' fully described. The description adds minimal extra meaning beyond confirming the lookup is by name or slug, which is already in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
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 'Get' and the resource 'one GTM tool by name or slug', which distinguishes it from sibling tools like compare_tools, search_tools, and list_changes. It also enumerates the specific data included (verified status, curation, product signals, etc.), leaving no ambiguity about the tool's 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 implies the tool is for retrieving a single known tool by name or slug, which contrasts with search_tools for discovering tools and compare_tools for comparisons. However, it does not explicitly state when not to use it or mention alternatives, so it stops short of full exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent detected changes to tracked tools (pricing, reachability, free-tier, deprecation), newest first. Optionally filter by kind.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Filter by change kind. | |
| limit | No | Max rows, 1–100 (default 20). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, and non-destructive behavior, so the description does not need to repeat safety info. It adds ordering ('newest first') and filtering semantics ('optionally filter by kind'), but does not disclose other behavioral details such as pagination, result shape, or limits beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the tool's purpose, content, ordering, and optional filtering. Every word earns its place with no filler or repetition.
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 list tool with two optional parameters, no output schema, and strong annotations, the description adequately covers what is listed and how it is ordered. It is slightly vague on 'recent' but overall sufficient; no critical gaps that would prevent correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full descriptions for both parameters (kind and limit), covering 100% of the schema. The description's mention of 'filter by kind' is redundant with the schema, and it adds no additional parameter-level detail or usage nuance beyond what schema descriptions already provide.
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 recent detected changes for tracked tools, enumerating specific change kinds (pricing, reachability, free-tier, deprecation) and ordering (newest first). This clearly distinguishes it from siblings like get_tool, search_tools, and compare_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 implies use when the user wants to see recent changes to tracked tools, but it does not explicitly address when to prefer this tool over alternatives or mention any exclusions. No comparison to sibling tools is provided, so guidance is limited to implicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the verified GTM-tools directory. Filter by keyword, category, tier (BADGE|listed|DEMOTE), verifiedOnly, or mcpOnly; sort by score (default), name, or g2. Returns ranked slim results. Use category + sort=score for 'best in category'.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort order (default score). | |
| tier | No | Curation tier filter. | |
| limit | No | Max results, 1–50 (default 10). | |
| query | No | Keyword matched against name, description, category, bestFor. | |
| mcpOnly | No | Only tools that publish an MCP server. | |
| category | No | GTM category (name or slug), e.g. 'Data Enrichment'. | |
| verifiedOnly | No | Only tools whose endpoint was reachable at last check. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context beyond annotations, such as that results are 'ranked slim results' from a 'verified' directory, which informs the agent about result characteristics. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences: purpose, filter/sort capabilities, return type, and a practical tip. It is front-loaded with the main verb and resource, with 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 7 optional parameters and no output schema, the description covers the core behaviors: filters, sort options, return type ('ranked slim results'), and a best-practice combination. It could be more explicit about result fields or pagination, but the mention of 'slim results' and the existence of get_tool for details makes it reasonably 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%, with each parameter already described (e.g., sort enum, tier enum, limit). The description merely restates the filter/sort options and adds a usage tip ('category + sort=score') but no new parameter-level semantics. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Search' and identifies the resource as 'the verified GTM-tools directory'. It clearly distinguishes this from siblings like compare_tools (comparing tools) and get_tool (retrieving a single tool) by focusing on discovery with filters and sorting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context for when to use the tool: searching the directory with various filters and sorts. It also gives a concrete usage example ('Use category + sort=score for best in category'). However, it does not explicitly mention when not to use it (e.g., when you need full details of a single tool), so it falls short of full alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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