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Onplana

by io.github.Onplana
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compose_evm_narrative

Generate a plain-language EVM narrative for a project and deliver it to the Agent inbox for review. Fetches BAC/EV/PV/AC/CPI/SPI/EAC and writes a PMO-quality prose document into the Agent Deliverables library. Returns the artifact id and conversation id once the narrative is drafted. Plan gate: aiCore (every plan). Access: callers who may read the project cost: org OWNER/ADMIN, or budget.read at their project role (by default project OWNER and MANAGER). The Onplana agent saves the draft, so it needs Contributor access or above on the project.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>"
    },
    "name": "compose_evm_narrative"
  }
}

Input Schema

NameRequiredDescriptionDefault
localeNoOptional. The language to write in, as an app language code: en, es, pt-BR, fr, ar, zh-CN, ja, de or it. Anything else, or nothing, is English.
projectIdYesID of the project to generate the EVM narrative for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / locale
      Added value: +{
+  "description": "Optional. The language to write in, as an app language code: en, es, pt-BR, fr, ar, zh-CN, ja, de or it. Anything else, or nothing, is English.",
+  "type": "string"
+}
  2. Added

TDQS

A4.1/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the data it reads (BAC/EV/PV/AC/CPI/SPI/EAC), the write side effects (artifact persisted to the Agent Deliverables library and delivered to the Agent inbox), the return values (artifact id, conversation id), and the exact permission/contributor requirements for a non-destructive but mutating operation.

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?

Purpose and delivery targets are front-loaded in the first sentence, followed by data sources, return values, and gating rules in a logical order. The 'Plan gate: aiCore (every plan)' fragment is slightly terse but each sentence carries usable information.

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?

For a two-parameter mutation tool with no output schema, the description covers inputs, side effects, return identifiers, and access requirements. It does not address repeat-invocation behavior (annotations mark idempotentHint=false, implying duplicate artifacts) or failure modes, which would complete the picture.

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?

Schema description coverage is 100% and both parameters (projectId, locale with its enumerated language list) are fully documented in the schema. The description adds no additional parameter semantics, so the baseline 3 applies.

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?

Names a specific verb and resource ('Generate a plain-language EVM narrative for a project') and states the delivery destinations (Agent inbox, Agent Deliverables library). It does not explicitly distinguish itself from related siblings like calculate_evm, critical_path_narrative, or leveling_narrative, so an agent must infer the boundary.

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 concrete preconditions for use: the aiCore plan gate, read access to project cost (org OWNER/ADMIN or budget.read at project role), and Contributor access on the project so the agent can save the draft. It stops short of naming when to prefer a sibling narrative tool or when not to use this one.

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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