Pushary

Cancel Pending Question

cancel_question

Idempotent

Retract a pending question so it can no longer be answered. Use this when a question became irrelevant before the user replied: the agent found the answer itself, the task was aborted, or a newer question supersedes it. Cancelling prevents a stale approval from arriving later and acting on work that has moved on. Only affects questions that are still pending; questions expire on their own 10 minutes after creation. Returns { cancelled: true } when a pending question was removed. False means it was already answered, expired, unknown, or unavailable; when status is unavailable, follow handoffAction and stop rather than opening another answer surface.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`correlationId`	Yes	The correlationId of the pending question to cancel, as returned by ask_user or send_notification

Output Schema

TableJSON Schema

Name	Required	Description
`hint`	No	What to do when cancellation could not safely inspect the question.
`status`	No	Present when Pushary could not safely read or fence the question state.
`cancelled`	Yes	True when a still-pending question was removed. False when it was already terminal, missing, or unavailable; inspect status and handoffAction when present.
`correlationId`	Yes	The question this result refers to, echoed back.
`handoffAction`	No	Stop rather than opening another answer surface when the question state is unavailable.

TDQS

A4.5/5.0

Behavior5/5

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

Goes beyond the annotations by disclosing that questions expire after 10 minutes, pending-only effects, return semantics for both cancel paths, and the needed unavailable-status behavior. This is not inferable from idempotentHint or destructiveHint alone.

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?

Front-loaded with the action and effect, then efficiently covers use cases, expiry, return semantics, and edge cases. Every sentence earns its place; no filler or repetition.

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

Completeness5/5

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

For a one-parameter, idempotent operation with an output schema, this covers when to call it, what it affects, what it returns, and what to do in the no-op/unavailable case. The only mild ambiguity is the exact shape of the false result, but the output schema covers return values.

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?

With 100% schema description coverage, the schema fully documents correlationId, its UUID format, and its meaning. The tool description adds essentially nothing about the parameter. Baseline 3 is appropriate.

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?

States a distinct verb and resource: 'Retract a pending question' with a clear effect ('can no longer be answered'). The use-case listing makes the purpose unmistakable and separates it from the ask/wait sibling tools.

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?

Explicitly gives when to use it: when a question became irrelevant before the user replied, with concrete triggers. It also gives an important exclusion—only pending questions are affected—and instructs the agent to stop rather than open another surface when status is unavailable, though it does not name sibling alternatives explicitly.

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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TDQS

A4.7/5.0

Disambiguation5/5

Each tool has a clearly distinct role: ask_user blocks for a decision, send_notification is one-way, wait_for_answer polls an existing question, cancel_question retracts a pending one, and propose_scope is a specialized ratification flow. The only potential overlap is ask_user versus propose_scope, but the scope-specific contract and 'call ONCE at the start' guidance make the boundary clear.

Naming Consistency5/5

All five tools follow the same imperative verb_noun snake_case pattern: ask_user, cancel_question, propose_scope, send_notification, wait_for_answer. Even though the verbs differ, the structure is uniform and predictable.

Tool Count5/5

Five tools is well-scoped for a push-notification and human-in-the-loop interaction server. There is no redundancy or padding; every tool maps to a distinct stage in the question/notification lifecycle.

Completeness5/5

The server covers the full interaction lifecycle: create a question (ask_user), wait for its answer (wait_for_answer), cancel it if obsolete (cancel_question), send one-way alerts (send_notification), and ratify scope before multi-step work (propose_scope). No obvious dead ends or missing critical operations exist for the stated purpose.

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