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Save an answer

save_answer
Destructive

Save the correct answer to a customer question, superseding any earlier saved answer to that question. This also queues replies to eligible customers waiting for that answer on connected messaging channels. Confirm the wording and these effects with the user before saving. Each call creates a new knowledge source and uses embedding credits; do not retry a successful save.

Input Schema

NameRequiredDescriptionDefault
answerYes
agent_idYesThe agent_id from list_agents.
questionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Goes well past the annotations by disclosing the destructive effect in concrete terms (earlier saved answer is superseded), an outward-facing side effect (queues replies to waiting customers on connected channels), a cost (embedding credits per call), and the reason not to retry (new knowledge source each call, matching idempotentHint=false).

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?

Four short sentences, front-loaded with the core action and its consequences, followed by the confirmation rule and the credit/retry caveat. No filler.

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 destructive, outward-facing, non-idempotent mutation with no output schema, the description covers the effects, the confirmation precondition, and the cost/retry pitfall. The remaining gap is return-value and partial-failure behavior, which is minor given the annotations already flag destructiveness.

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?

Only agent_id is documented in the schema (33% coverage) and the description merely points back to list_agents implicitly via the schema. The description implies that question and answer are free text and that answer wording matters, but adds no format or length guidance beyond the structured constraints.

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

Purpose4/5

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

States a specific verb and resource (save the correct answer to a customer question) plus the superseding semantics, which is more than a restatement of the name. It does not, however, draw the boundary against the sibling add_knowledge, leaving the agent to infer which one creates vs. replaces knowledge.

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?

Gives concrete operating guidance: confirm wording and effects with the user before saving, and do not retry a successful save. Missing an explicit 'use add_knowledge instead when...' routing rule, so the alternative is implied rather than stated.

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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