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Obra CTO

Obra CTO

by lilycip
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Score Build Readiness

score_build_readiness

Scores your codebase's build readiness (0-100) with dimension breakdown, evidence grades, and risk register. Optionally enhances reliability evidence with test results.

Instructions

Produce the Obra CTO Score (0 to 100) with a per-dimension breakdown, evidence grades, and a Top Risks register. Scan runs automatically. If you ran run_tests first, pass its numbers so reliability becomes grade-A evidence.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "score_build_readiness"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathNoProject root. Defaults to the current working directory.
stageNoCalibrate expectations to your stage: prototype, mvp, or growth. Defaults to a detected guess.
qualitativeNoYour structured security and architecture assessment from prepare_code_review. Supplying it upgrades those dimensions to grade A.
tests_totalNoTotal tests, from a prior run_tests call.
tests_failedNoFailing tests, from a prior run_tests call.
tests_passedNoPassing tests, from a prior run_tests call.
write_reportNoWrite the report to .obra/ in the project (default true), so the Obra CFO can read it later. Set false to skip writing.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the scan runs automatically and writes a report to .obra/ (via write_report parameter). It also explains how supplying test numbers and qualitative assessments affects evidence grading. No destructive actions are implied; the description is sufficiently transparent for a scoring 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?

The main description is two sentences with no waste, clearly stating the output and a critical workflow hint. Parameter descriptions are not repeated in the main text but are part of the schema, keeping the overall description concise and front-loaded.

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?

Given the tool's complexity (7 parameters, nested objects, no output schema), the description provides enough context to use it correctly: it explains the output format (score, breakdown, risks), the automatic scan, and how to leverage prior tool outputs. However, it could be slightly more explicit about the return structure (e.g., JSON object) but overall is complete.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3. The description adds substantial value beyond the schema: it explains that stage defaults to a detected guess, that qualitative input from prepare_code_review upgrades dimensions to grade A, and that test numbers come from a prior run_tests call. Each parameter's purpose and cross-tool dependency are clarified.

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 clearly states the tool produces an Obra CTO Score (0-100) with a per-dimension breakdown, evidence grades, and Top Risks register. This specific verb+resource+output distinguishes it from sibling tools like scan_project and run_tests, which have different purposes.

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 advises the agent to pass test numbers from a prior run_tests call to upgrade reliability to grade-A evidence. It also mentions that the qualitative input can come from prepare_code_review, implying a workflow. However, it does not explicitly state when not to use this tool or list alternatives.

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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