ai-agent-channel

awaiting_ack

List proposals needing your role's agree, reject, or needs_changes decision, filterable by author and pin. Find outstanding decision debts while ignoring non-decisions and already-voted items.

Instructions

List proposals (kind='proc') addressed to a role (defaults to yours) that still need that role's agree/reject/needs_changes. These are debts just like open_obligations; check both. Four things are deliberately NOT listed, because none of them is a decision anyone is waiting for: a nudge (sent with about_message_id — it asks about another message, and its own record could never be closed by anything), a proposal opened for reading (decision_requested=false), a superseded one, and one this role has already voted on — unless the body was re-issued since, which puts the question back. 'from_role' filters by AUTHOR, which is how you measure what YOU have hung on other people: filtering by addressee alone means the role that sends the most has the emptiest list, and reads its own zero as 'nothing outstanding from me'. 'pin_key' narrows to one pin's round. Entries that are ALSO action_required carry 'obligation' — the state of the work half ({status, resolved_by, resolved_at, confirmed}). The two contours stay independent (closing the work must not silently cancel the other side's obligation to answer), but a listing that cannot show one from the other is how a record whose work was finished and confirmed days ago still reads as unfinished. Stuck with an entry whose subject no longer exists — the edition it points at was replaced or withdrawn? That is what acknowledge(decision='void') is for. Voting on it would record consent to text nobody can read; leaving it is how a list stops meaning anything. Optional 'fields' projects the response: a list of field names, or the single value 'headers' for the usual listing set (everything except the bodies). Omit it and the full record comes back exactly as before. Use it when a listing over a long history would otherwise be too large to return — bodies dominate the size, and a 'which messages' question rarely needs them; fetch the ones you want individually afterwards.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`fields`	No
`pin_key`	No
`to_role`	No
`from_role`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and delivers: it enumerates four things deliberately excluded and why, explains that the work/answer contours stay independent, notes that re-issued bodies re-list an already-voted entry, and describes the 'obligation' field's shape. This is unusually rich behavioral disclosure for a read tool.

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 first sentence is well front-loaded, but the body is long and digressive, with philosophical asides ('reads its own zero as nothing outstanding from me') and a run-on stretch on contour independence. Much earns its place, but it is not tightly trimmed.

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 5-parameter tool with 0% schema description coverage and an output schema, the description covers the tricky parameters, the exclusion rules, and even the 'obligation' return field. Only the missing explanation of 'limit' keeps it from being fully complete.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate and largely does: from_role is clarified as filtering by AUTHOR (a counterintuitive point with an explicit rationale), pin_key narrows to one round, and fields accepts a list or the literal 'headers'. Only 'limit' is left unexplained, keeping this short of a 5.

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 opening sentence gives a specific verb and resource ('List proposals (kind=\'proc\')') plus the exact filter (still need a decision) and scope. It explicitly positions itself against open_obligations ('check both'), so an agent can distinguish it from siblings without opening a schema.

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

Usage Guidelines5/5

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

It tells the agent when to reach for this tool ('debts just like open_obligations'), names the sibling to pair it with, and routes edge cases to alternatives (acknowledge(decision='void') for entries whose subject no longer exists). The fields projection includes an explicit 'use it when' condition.

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