tower-mcp

propose_intent

State your planned work in plain English before researching or writing; it returns anyone already doing the same task, matched by meaning, so duplicate efforts are caught early.

Instructions

BEFORE you research or write anything: say in plain English what you plan to work on. Returns anyone already doing the same work, matched on meaning rather than file paths — so it catches a duplicate even when you would have picked a different filename. One call per task; it is the cheapest check Tower offers and the only one that fires before your tokens are spent.

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": {
      "agentId": "<agentId>",
      "repo": "<repo>",
      "purpose": "<purpose>"
    },
    "name": "propose_intent"
  }
}

Input Schema

Name	Required	Description	Default
`repo`	Yes
`repoId`	No
`agentId`	Yes
`purpose`	Yes
`projectId`	No

Output Schema

Name	Required	Default
`matches`	Yes
`duplicate`	No
`recommendation`	No	proceed

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 30, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses what comes back (anyone already doing the same work, semantic matching) and a cost/ordering trait, but leaves unresolved whether the call registers durable state, whether it mutates anything, or whether repeated calls are idempotent — key behavior for a 'propose' tool.

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?

Three dense sentences with the imperative timing constraint front-loaded. Every clause adds routing or behavioral information; nothing is padding.

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?

An output schema exists, so return values needn't be explained, and usage timing is well covered. However, with zero annotation coverage and five undocumented parameters, an agent still lacks guidance on what the identifier fields mean and whether the call has side effects.

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

Parameters2/5

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

Schema description coverage is 0% across 5 parameters (agentId, repo, repoId, purpose, projectId). The description only loosely implies the purpose field via 'say in plain English what you plan to work on' and says nothing about repo, repoId, projectId, or agentId semantics, so it fails to compensate for the coverage gap.

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?

The description gives a concrete verb and resource: state in plain English what you plan to work on before researching or writing. It also distinguishes the matching behavior ('matched on meaning rather than file paths') from path-based checks, though it never names the sibling tools (claim_intent, check_collision) it sits beside.

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?

It states the timing condition clearly ('BEFORE you research or write anything'), the call frequency ('One call per task'), and the value rationale ('cheapest check', 'fires before your tokens are spent'). It stops short of naming explicit alternatives or when-not-to-use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.