Discover Drawcall workflows for 3D apps and asset creation; read APIs and approve CLI logins.
Scored across 3 tools
The three tools target distinct actions: authentication approval, documentation search, and documentation reading. approve_login is clearly separate from the skill tools, and search_skills vs read_skills have a discover-then-read relationship that descriptions make clear, though an agent could momentarily conflate searching with reading.
read_skills and search_skills follow a consistent verb_noun snake_case pattern, but approve_login is a verb_noun compound that reads slightly differently (approve a login rather than an action on a 'login' resource). The deviation is minor and all names remain predictable and readable.
Three tools is quite thin for a server named Drawcall whose descriptions imply a broader asset, workflow, and API documentation ecosystem. It is borderline but defensible if the scope is strictly authentication plus skill discovery.
The surface covers login approval and skill search/read, but there is no tool to list skills, inspect a specific asset, or complete the auth flow programmatically despite the description telling the agent to run a separate CLI command. Notable gaps for a documentation-discovery server.
Approve a pending Drawcall CLI login as your connected account. This grants the CLI a full account session. Only approve the user_code printed by the user's current drawcall auth login command. After approval, run drawcall auth complete in that CLI.
| Name | Required | Description | Default |
|---|---|---|---|
| user_code | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare a non-readOnly, non-idempotent, non-destructive mutation, and the description adds meaningful context beyond them: the operation 'grants the CLI a full account session,' which is a security-relevant consequence worth surfacing. It does not detail failure behavior for an invalid or expired code, leaving a minor gap.
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 short sentences, front-loaded with the action, each contributing distinct information (effect, precondition, follow-up step). No repetition of the title or wasted phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter mutation tool with no output schema, the description covers purpose, security consequence, parameter origin, and the required follow-up command. Missing only edge-case behavior (what happens with an already-used or invalid code), which is minor given annotation coverage of safety traits.
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 carries the burden for user_code. It helpfully identifies the value's origin ('printed by the user's current drawcall auth login command') but adds no format, length, or validity details, and the schema only declares it as a bounded string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Approve a pending Drawcall CLI login') and immediately clarifies the scope via 'as your connected account.' An agent can tell exactly what action occurs, and the sibling tools (read_skills, search_skills) are unrelated, so no differentiation burden exists.
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 clear procedural context: approve only the user_code from the user's current 'drawcall auth login' command, then run 'drawcall auth complete'. This is effectively a when-to-use plus an implicit when-not ('Only approve...'). No named alternative tool exists to route against, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read a guide for its workflow and prerequisites, or a declaration for API details. When the workflow needs user action, give the documented command or URL as the next step. A package path lists its skills and import paths; a SKILL.md gives its full guide. Paths come from search results and read_skills listings; listing names are relative to the path that was read.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | e.g. /@drawcall/physics@0.1.0/types/RigidBody |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds real behavior beyond that: a package path yields a listing of skills/import paths while a SKILL.md yields a full guide, and it explains path provenance and relative naming.
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?
Four sentences, purpose front-loaded, and each sentence carries distinct information about path types, provenance, and follow-up action. Slightly dense and self-referential ('read_skills listings') but 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?
With no output schema, the description correctly takes on the burden of explaining return shapes (guide, declaration, package listing). It covers navigation, provenance, and next-step behavior; only the underlying concept of a 'skill' remains abstract.
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% and the single parameter carries an example, so the baseline is 3. The description goes further by explaining what different path forms return and where valid paths originate, adding genuine meaning 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?
States a specific verb (read) and resource (skills/guides/declarations), and clarifies what is returned depending on the path type (package listing vs SKILL.md guide). It implicitly separates itself from search_skills by noting paths 'come from search results', though it never names the sibling 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?
Usage is implied rather than stated: paths 'come from search results and read_skills listings' suggests search_skills should run first. It also gives post-read guidance ('give the documented command or URL as the next step') but no explicit when-not-to-use or direct alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Drawcall workflows and APIs for apps, games and assets. Discover asset sourcing as well as runtime libraries. Source visual content from @drawcall/market first. When its candidates do not fit, consult @drawcall/generate for generation options and prerequisites before settling on a fallback. Reserve hand-authored geometry for gameplay structure or explicitly procedural content. @drawcall/rig adds skeletons and skin weights when needed. This searches documentation, not Market inventory: read the guides to find and inspect actual assets. Search covers all supported packages automatically, including in an empty project. Returns up to five paths with excerpts; read_skills provides the full workflows and APIs.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What you want to implement or learn how to do |
| Name | Required | Description |
|---|---|---|
| results | Yes | The five best, best first, at most one per document |
| packages | Yes | Every selected package, in selection order |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/openWorld/no-destructive, so the safety profile is covered. The description goes beyond them by disclosing that the search spans all supported packages automatically (even in an empty project) and returns up to five paths with excerpts, which is meaningful behavioral context.
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?
Purpose and the key constraint ('searches documentation, not Market inventory') are front-loaded, but eight sentences for a single-parameter search tool includes some padding and restatement. The mid-section asset-sourcing advice is useful routing but makes the block longer than needed.
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 fully explained, yet the description still notes the five-path excerpt limit and directs the agent to read_skills for full content. Scope, sibling routing, and result characteristics are all covered; only minor details like exact matching behavior are absent.
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?
There is only one parameter and schema description coverage is 100%, with the schema already explaining the query field as 'What you want to implement or learn how to do'. The description adds no syntax, format, or scoping constraints beyond that, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (Search) and resource (Drawcall workflows and APIs), plus the domain (apps, games, assets). It explicitly distinguishes itself from the sibling read_skills ('read_skills provides the full workflows and APIs') and clarifies it searches documentation, not Market inventory, so an agent can select it without opening either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives explicit routing rules: source visual content from @drawcall/market first, fall back to @drawcall/generate when candidates don't fit, reserve hand-authored geometry for gameplay structure, and use @drawcall/rig for skeletons/skin weights. It also names the escalation path to read_skills for full workflows, leaving nothing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
search_skills1 field changedInput schema / additionalPropertiesAdded value: +falsesearch_skills4 fields changedInput schema / properties / packagesRemoved value: -{
- "items": {
- "description": "An npm package as name@version (the installed version), or a bare name for its latest",
- "type": "string"
- },
- "maxItems": 200,
- "minItems": 1,
- "type": "array"
-}Input schema / properties / query / descriptionPrevious value: -"One concrete question, goal or symptom"New value: +"What you want to implement or learn how to do"Input schema / requiredPrevious value: -[
- "query",
- "packages"
-]New value: +[
+ "query"
+]Output schema / properties / packages / descriptionPrevious value: -"Every requested package, in request order"New value: +"Every selected package, in selection order"approve_loginread_skillssearch_skillsDiscover atmospheric 3D worlds, read controls, and build and publish authorized environments.
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