Content Plan Builder
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'plan_from_content' has a single, clearly defined purpose of generating Asana project plans from content, making disambiguation perfect.
Naming Consistency5/5Since there is only one tool, naming consistency is inherently perfect. The tool name 'plan_from_content' follows a clear verb_noun pattern (plan from content), and there are no other tools to cause inconsistency.
Tool Count2/5A single tool for a server named 'Content Plan Builder' feels too thin for the apparent scope. The tool handles multiple operations (generate, preview, create), but these are bundled into one tool, suggesting the server might be under-scoped. Typically, such operations could be separate tools for better modularity and clarity.
Completeness3/5The tool covers core generation and creation operations for Asana project plans, but there are notable gaps. For example, there are no tools for updating, deleting, or managing existing plans, which are common in project management domains. This could lead to dead ends for agents trying to modify or remove plans.
Average 3.8/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's operations and output structure but lacks details on permissions, rate limits, error handling, or whether 'create' requires authentication (though asanaAccessToken parameter hints at this). It adds some context but doesn't fully cover behavioral traits for a complex tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with clear sections for purpose, plan details, operations, and a call-to-action. Every sentence adds value, though it could be slightly more concise by integrating some details more tightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no annotations, no output schema), the description is moderately complete. It covers purpose and operations but lacks details on authentication requirements, error conditions, output format specifics, or how the AI generation works. Without annotations or output schema, more behavioral context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 9 parameters. The description adds minimal parameter semantics by mentioning 'arbitrary content' and listing content types, but doesn't provide additional meaning beyond what the schema provides. The baseline of 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate Asana project plans from arbitrary content (text, PDF, DOCX, transcripts)' with specific details about what the plans include (5 top-level tasks with subtasks, time estimates, role assignments, dependencies, SMART goals). It distinguishes itself by specifying content types and plan structure, though no siblings exist for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage guidance by listing three operations (generate, preview, create) with brief explanations, and mentions 'Call without parameters for interactive discovery.' However, it doesn't explicitly state when to use each operation versus alternatives or provide exclusions, which prevents a perfect score.
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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