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q_validate_start

Start a background validation run on a plan file, returning a job_id immediately. Agents independently review and deliberate in rounds, with options for extended or verbose modes.

Instructions

Start a q-validate run in the background. Returns {"job_id": str} immediately. Each agent independently reviews the plan file, then deliberates across rounds. Round 1 is structurally bias-free; later rounds embed each agent's own prior plus peers' priors. Retrieve results by calling q_await with the returned job_id.

Between the start and the await, the caller is expected to form its own review — this is the structural anti-bias gate.

extended runs 4 rounds with a stance rotation at round 3 (agents swap stances and re-examine all priors); the default is 2 rounds with no rotation. mode is 'revise' (agents soften/strengthen in light of peers) or 'critique' (agents attack peer points).

verbose defaults to false: the council writes terse output (no padding, path:line over pasted code, later rounds omit restating unchanged points). Set true only for the full unabridged deliberation — a much larger matrix.

Optionally assign stances per agent via roles, a list of 'stance:agent' strings (stances: skeptic, architect, security, maintainer, analyst, neutral, visionary, pioneer).

gemini_model, when supplied, runs the gemini seat on that agy model for this invocation only (an id exactly as printed by agy models, e.g. 'claude-opus-4-6-thinking').

Expected wall-clock to completion: 1-8min default; 4-15min when extended=true. Pick extended deliberately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdYes
hostNo
modeNorevise
rolesNo
agentsNo
skip_ghNo
verboseNo
extendedNo
plan_pathYes
no_contextNo
gemini_modelNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It comprehensively explains the background execution, immediate return of job_id, the bias-free first round and later rounds embedding priors, the extended mode's 4 rounds and stance rotation, the verbose output toggle, and the gemini_model override for this invocation. It also discloses expected wall-clock times and the anti-bias gate expectation, making the tool's behavior highly transparent.

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?

The description is detailed but well-structured, front-loading the core behavior and return value before diving into options. It uses clear paragraphs and imperative sentences that earn their place. While somewhat long, the length is justified by the tool's complexity, and it could be slightly more concise without losing essential information.

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?

Given the tool's complexity (11 parameters, no schema descriptions), the description covers the main workflow and several key parameters, and provides expected wall-clock times. However, it omits explanations for critical parameters like plan_path and cwd, and does not clarify the exact output format beyond job_id (though q_await likely handles results). The description is strong on purpose and behavior but incomplete in parameter coverage, so it is not fully complete for an agent to confidently invoke the tool correctly.

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%, so the description must compensate for parameter documentation. It explains extended, mode, verbose, roles, and gemini_model in detail, but leaves essential parameters like plan_path, cwd, host, agents, skip_gh, and no_context unexplained. The required plan_path is only referred to generically as 'plan file', which is insufficient for an agent to know exactly what to provide. The description only partially covers the 11 parameters, making parameter semantics incomplete.

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 it starts a q-validate run in the background and returns a job_id immediately. It describes the process of agents reviewing the plan file and deliberating, which distinguishes it from sibling tools like q_plan_start, q_brainstorm_start, and q_review_start. The tool's purpose is unambiguous and specific.

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 provides explicit guidance on retrieving results via q_await with the returned job_id and explains the structural anti-bias gate that the caller should form its own review between start and await. It also advises when to use extended mode ('Pick extended deliberately') and explains the default vs extended rounds. However, it does not explicitly contrast this tool with sibling start tools, relying on tool names for differentiation.

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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