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peer_ask

Ask a peer AI agent for code review, planning, or debugging by providing a question, repository path, and relevant files. Includes context and task details to guide the response.

Instructions

Before calling: read relevant source files and attach full contents via files. Pass complete diffs/logs — never prose summaries. Set task with goals, affected behavior, and specific concerns. General knowledge or grounded Q&A — routes to Antigravity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesRequired. The decision or question, plus what constraints and tradeoffs the answer must address.
repo_pathYesAbsolute path to the repository root the peer should work in (e.g. /home/user/my-app).
contextNoBackground the peer needs: prior decisions, relevant code paths, docs links, or constraints.
filesNoChanged source files and binary attachments (screenshots, PDFs). Use correct file extensions for images/PDFs and pass base64 or data-URI content.
taskNoHuman-readable session label: what you are trying to achieve, affected behavior, and specific concerns for the peer.
idempotency_keyYesStable key for this operation (e.g. review-auth-jwt-1). Reuse the same key when retrying after timeout.
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the routing behavior to Antigravity and mentions automatic staging of binaries. However, it omits details on mutation, authentication, rate limits, or side effects beyond the routing.

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

Conciseness3/5

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

The description is two sentences but dense and run-on. It mixes instructions, conditions, and routing info in a stream-like manner. Could be better organized with bullet points or clearer separation of purpose vs. usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, no output schema, and complex routing behavior, the description should explain what the tool returns or the outcome. It lacks any mention of return value, response format, or post-call state, leaving the agent uncertain about what to expect.

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%, so the schema already explains all parameters. The description adds minimal extra meaning (e.g., 'Binary attachments are staged to disk...' in the files parameter is already covered by schema). Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description focuses on pre-call instructions rather than stating the tool's purpose. It vaguely mentions 'General knowledge or grounded Q&A — routes to Antigravity', but the primary verb and resource are unclear. It does not effectively distinguish from sibling tools like peer_debate or peer_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit before-calling steps (read files, attach content, set task) and mentions routing to Antigravity for certain queries. However, it lacks a clear 'when to use' vs 'when not to use' and does not reference specific sibling tools as 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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