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Compose and export a project report PDF

produceProjectReport
Idempotent

Compose a project report PDF. Pass projectId or project; with neither, the result lists projects and no meter is spent. preview=true composes without spending. confirm=true exports, spends records.exports, and is irreversible. Returns a signed download URL, never PDF bytes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailYesdetailed
confirmYesWhen true, compose (if needed), save, export PDF, and return a download URL. Required when preview is false. Spends records.exports and cannot be undone.
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
previewYesWhen true, compose only — no export meter spend and no download URL.
projectNoProject name to match, when you do not have the UUID. Case-insensitive; an exact name wins over a partial one. Matching more than one lists the candidates instead of guessing.
requestNo
audienceYesowner
planNameNo
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
projectIdNoProject UUID. Omit if you pass `project`.
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "audience",
-  "detail",
-  "preview",
-  "confirm",
-  "context"
-]New value: +[
+  "audience",
+  "detail",
+  "preview",
+  "confirm",
+  "context",
+  "llm_model"
+]
  2. Changed3 schema fields changed
    • addedInput schema / properties / project
      Added value: +{
+  "description": "Project name to match, when you do not have the UUID. Case-insensitive; an exact name wins over a partial one. Matching more than one lists the candidates instead of guessing.",
+  "maxLength": 200,
+  "minLength": 1,
+  "type": "string"
+}
    • addedInput schema / properties / projectId / description
      Added value: +"Project UUID. Omit if you pass `project`."
    • changedInput schema / required
      Previous value: -[
-  "projectId",
-  "audience",
-  "detail",
-  "preview",
-  "confirm",
-  "context"
-]New value: +[
+  "audience",
+  "detail",
+  "preview",
+  "confirm",
+  "context"
+]
  3. First observed

TDQS

A3.5/5.0
Behavior1/5

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

The description claims confirm=true 'spends records.exports, and is irreversible', which directly contradicts the annotations' idempotentHint=true and destructiveHint=false. An irreversible meter-spending operation is neither idempotent nor non-destructive from the caller's perspective. This is a clear annotation contradiction, so the score is minimal.

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

Conciseness5/5

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

The description is a single, tight paragraph that front-loads the core action and then clarifies the critical decision points (project selection, preview vs confirm, return format). Every sentence carries essential information with no filler.

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

Completeness3/5

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

For an 11-parameter tool with no output schema, the description covers the key control flow (preview/confirm, project matching, URL return) but omits details about several parameters (request, planName, audience, detail, conversation_id). The schema provides some descriptions, but the lack of guidance on how these parameters interact (e.g., how request relates to report content) leaves gaps. An agent would need to infer several parameter meanings from the schema alone.

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

Parameters3/5

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

The description adds meaning for projectId/project selection, preview, and confirm beyond the schema, particularly the meter-spend and irreversibility of confirm. However, it does not elaborate on request, planName, audience, detail, or conversation_id. Schema coverage is 64%, so the description partially compensates but leaves the remaining parameters to the schema's own descriptions.

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

Purpose5/5

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

The description states a specific action (compose and export a project report PDF) and resource, and distinguishes between preview and confirm modes. It also clarifies the return type (signed URL, not bytes) and the fallback behavior when neither projectId nor project is provided. No sibling tool overlaps with this function, so the purpose is unambiguous.

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

Usage Guidelines4/5

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

The description explicitly explains when to use preview=true (compose without spending) vs confirm=true (export, spends meter, irreversible). It also notes that omitting both projectId and project lists projects without spending. However, it does not mention when to avoid using the tool entirely or direct alternatives, though the clear mode guidance suffices for most calls.

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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