Bucky

Compose and export a project report PDF

produceProjectReport

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

Name	Required	Description	Default
`detail`	No		detailed
`confirm`	No	When true, compose (if needed), save, export PDF, and return a download URL. Required when preview is false. Spends records.exports and cannot be undone.
`context`	Yes	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."
`preview`	No	When true, compose only — no export meter spend and no download URL.
`project`	No	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.
`request`	No
`audience`	No		owner
`planName`	No
`projectId`	No	Project UUID. Omit if you pass `project`.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 31, 2026

changedInput schema / required

Previous value: -[
-  "audience",
-  "detail",
-  "preview",
-  "confirm",
-  "context"
-]New value: +[
+  "context"
+]

Changed2 schema fields changedOct 26, 2026

removedInput schema / properties / llm_model

Removed 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",
-  "llm_model"
-]New value: +[
+  "audience",
+  "detail",
+  "preview",
+  "confirm",
+  "context"
+]

Changed1 schema field changedOct 12, 2026

removedInput schema / properties / conversation_id

Removed 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"
-}

Changed4 schema fields changedSep 26, 2026

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"
+]

Changed3 schema fields changedSep 21, 2026

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"
+]

First observedSep 1, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description carries full behavioral disclosure: meter spend on records.exports, irreversibility of export, the listing fallback, and the concrete return shape (signed download URL, never PDF bytes). This goes well beyond the {readOnlyHint:false, destructiveHint:false, openWorldHint:true} annotations; the 'irreversible' note is consistent with an additive, non-destructive export rather than a contradiction.

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?

Front-loaded with purpose, then progressively discloses the decisions that matter (project selection, preview vs confirm, spend/return). Every sentence earns its place; no redundant restatement of the title.

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

Completeness4/5

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

Strong for a 9-parameter mutation tool with no output schema — return format, cost, and reversibility are all covered. The remaining gap is the opaque `request` parameter and the unexplained content-shaping params (audience, detail, planName).

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 real meaning for the key params (projectId/project resolution, the preview/confirm coupling) and even documents the no-project fallback that the schema lacks. However, it leaves `request`, `audience`, `detail`, and `planName` unaddressed, and `request` has no schema description at all, so the agent cannot infer its role.

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

Purpose4/5

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

States a specific verb+resource: 'Compose a project report PDF,' which clearly distinguishes this from analysis/context siblings. However, it does not explicitly compare itself to any sibling tool, leaving that differentiation to inference.

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

Usage Guidelines5/5

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

Explicitly defines the operating modes: pass projectId or project, get a project listing with no spend if neither, preview=true to compose without spending, and confirm=true to export and spend. An agent knows precisely which path to take for each goal.

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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Compose and export a project report PDF

Input Schema

Schema Changelog

TDQS

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