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by com.buckybuild
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Get project context bundle

getProjectContext
Read-onlyIdempotent

Load one project with analysis envelope, compact agentStatus, document summaries, evidence summaries, the project memory digest, and external_ref when the project was imported from another system. Pass include for optional sections: tasks, members, insights, capital, visualEvidence. Default is none, so the payload stays the same as a call without include. Writes to those sections stay on the Bucky CLI. You do not need a UUID: pass project with the name the user said, or call with neither and the result lists their projects to choose from. Use before composing reports or after scheduling analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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."
includeYesOptional extra sections. Default is none, so the payload matches a call without include. tasks, members, insights, capital, and visualEvidence each reuse the matching product read — they are not separate tools. Writes stay on the Bucky CLI.
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.
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`.
evidenceLimitYes
documentsLimitYes
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. Changed2 schema fields changed
    • addedInput schema / properties / include
      Added value: +{
+  "default": [],
+  "description": "Optional extra sections. Default is none, so the payload matches a call without include. tasks, members, insights, capital, and visualEvidence each reuse the matching product read — they are not separate tools. Writes stay on the Bucky CLI.",
+  "items": {
+    "enum": [
+      "tasks",
+      "members",
+      "insights",
+      "capital",
+      "visualEvidence"
+    ],
+    "type": "string"
+  },
+  "type": "array"
+}
    • changedInput schema / required
      Previous value: -[
-  "documentsLimit",
-  "evidenceLimit",
-  "context",
-  "llm_model"
-]New value: +[
+  "documentsLimit",
+  "evidenceLimit",
+  "include",
+  "context",
+  "llm_model"
+]
  2. 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: -[
-  "documentsLimit",
-  "evidenceLimit",
-  "context"
-]New value: +[
+  "documentsLimit",
+  "evidenceLimit",
+  "context",
+  "llm_model"
+]
  3. Changed2 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"
+}
    • changedInput schema / properties / projectId / description
      Previous value: -"Project UUID to load. Omit to have the user pick from their projects."New value: +"Project UUID. Omit if you pass `project`."
  4. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral facts: default `include` yields a stable payload, writes to those sections stay on the Bucky CLI, and name matching prefers exact over partial and lists candidates on ambiguity. It omits rate/limit or auth behavior.

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

Conciseness4/5

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

Front-loaded with the returned payload then the parameter guidance, and every sentence carries information. It is on the long side but not padded, with no restatement of the name or 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?

With no output schema, the description compensates by enumerating exactly what the bundle contains, and it covers the optional include sections and identity fallback. Only the odd required telemetry parameters (context, llm_model) are left entirely to the schema.

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

Parameters4/5

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

Schema coverage is 75%, and the description adds real meaning for the two ambiguous parameters: `include` semantics (default none, sections reuse matching product reads rather than separate tools) and `project` matching rules. It does not explain the telemetry-style required fields, which the schema handles.

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?

States a specific verb and resource ('Load one project') and enumerates the exact bundle contents (analysis envelope, agentStatus, document/evidence summaries, memory digest, external_ref). An agent can distinguish this from siblings like produceProjectReport or runFeasibilityAnalysis without reading the schema.

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?

Gives explicit timing ('Use before composing reports or after scheduling analysis') and handles the identity ambiguity ('pass `project` with the name the user said, or call with neither and the result lists their projects'). It does not name an alternative sibling by name, keeping it short of a 5.

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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