tool-design-errors

Tool error design

An agent that receives only 429 either retries in a tight loop or gives up. An agent that receives "Rate limited. Wait 30 seconds, or reduce batchSize to 50 and retry" makes a better second call. Give every error a class, a reason, and the next call to make. Design the failure paths with the same care as the success path.

Procedure

1. List every way the tool can fail: bad input, missing prerequisite, not found, ambiguous match, upstream unavailable, rate limit, timeout, permission denied, missing scope, partial completion.
2. Classify each failure into exactly one class (below). The class tells the agent whether to retry, change the call, ask the user, or have the user re-authenticate.
3. Write the recovery text for each failure: what went wrong, why, and the exact next call.
4. Decide the ambiguity policy for any natural-identifier input: thresholds for auto-accept, confirm, and reject.
5. Decide the degradation policy for multi-source or multi-step tools: what the tool returns when part of the work fails.
6. Test by reading the error cold: could an agent with only the tool description and this error message make a better second call? If not, rewrite it.

Rules with examples

The names in parentheses are the pattern names that the tool-design skills share.

All examples use one error envelope: class, message, reason, recoverySteps, and, where they apply, retryAfterSeconds, options, or suggestions. Use the same envelope in every tool in the set.

Every error carries a class (Error Classification)

Class	Meaning	Agent should
retryable	Transient. Likely to succeed later	Wait retryAfterSeconds, retry
permanent	Will not succeed without a changed call	Change parameters or tool
userInput	Needs a human decision	Ask the user
authRequired	Credential or scope missing or expired	Ask the user to reconnect access

Use the same class vocabulary in every tool in the set. Map upstream errors onto it inside the tool, so the agent never sees vendor-specific codes. Retryable errors always carry retryAfterSeconds.

Every error guides recovery (Recovery Guide)

Use structure, not prose:

{
  "class": "permanent",
  "message": "User not found",
  "reason": "No user matches \"jon smith\"",
  "recoverySteps": [
    "Call search_users(query=\"jon smith\") to list candidates",
    "Retry with the user's email address instead of a display name"
  ],
  "suggestions": [{ "id": "usr_1", "name": "Jon Smyth", "email": "jon@example.com" }]
}

Include concrete tool names and parameter values, not "check your input". Name alternative tools when one exists. For a rate limit, say how long to wait and what size to reduce.

Ambiguity returns options, never a guess (Confirmation Request)

When a natural identifier matches more than one record, do not pick one. Return the matches with enough detail to tell them apart (name, email, last activity), cap the list at five to ten, and state the exact call to make for each option:

{
  "class": "userInput",
  "message": "3 contacts match \"Alex\"",
  "reason": "The name \"Alex\" is not unique",
  "options": [
    { "contactId": "c_1", "name": "Alex Kim", "email": "alex.kim@example.com" },
    { "contactId": "c_2", "name": "Alex Reyes", "email": "areyes@example.com" }
  ],
  "recoverySteps": ["Call update_contact(contactId=...) with one of the ids above"]
}

Zero matches is a permanent error with suggestions, not an empty list that reads as success.

Thresholds decide when to ask (Fuzzy Match Threshold)

Confirming every match is slow. Never confirming is dangerous. Pick thresholds and document them. A reasonable starting point:

• Above 90% confidence: auto-accept, and log the match for audit.
• 50% to 90%: return the candidates as a confirmation request.
• Below 50%: reject with a "try a different identifier" recovery step.

Expose the threshold as a parameter with a safe default when callers need to tune it. Command tools with irreversible effects should set the auto-accept bar higher than query tools.

Return what worked (Graceful Degradation)

A tool that aggregates from several sources or performs several steps returns the parts that succeeded, names the parts that failed, states completeness, and says how to get the rest:

{
  "completeness": "partial",
  "crm": { "...": "..." },
  "billing": null,
  "errors": [
    {
      "source": "billing",
      "class": "retryable",
      "reason": "Billing service unavailable (503)",
      "retryAfterSeconds": 60
    }
  ],
  "recoverySteps": ["Call get_unified_profile again in 60 seconds for billing data"]
}

A total failure that hides a successful partial result wastes the work already done and the tokens already spent.

Provide an alternative when the primary is down (Fallback Tool)

For critical capabilities, define a fallback order (slack, then email, then sms). Either switch transparently and report channelUsed and wasFallback: true, or return a permanent error that names the fallback tool to call. Never fall back silently to a command whose side effects differ from the one requested.

Timeouts are errors too

A timeout returns a retryable error that says what timed out, how long the limit is, whether partial results are attached, and whether an async variant exists. See tool-design-execution for the boundary itself.

Anti-patterns

• Passing the upstream exception string or HTTP status through as the error.
• "Invalid input" with no field name and no valid values.
• Picking the first fuzzy match on a command tool.
• Throwing on the first failed item in a batch.
• A retryable error with no retryAfterSeconds, so the agent retries immediately.
• Success-shaped responses for failures ({ "items": [] } when the query was invalid).
• Recovery text written for the developer ("see logs") instead of the agent.

On Runtype

What the model receives

• Runtype classifies every failed tool call. The model receives { error, errorType }, where errorType is one of auth, rate_limited, upstream_4xx, upstream_5xx, timeout, invalid_args, not_configured, aborted, or unknown. Runtype sets it from the HTTP status first, then from the error text. It does not tell the model whether to retry. Your classes add to errorType: return the matching status (429 with retryable, 401 or 403 with authRequired, 400 or 422 with permanent) and put your class and recovery steps in the error body.
• For an external tool, shape the error in your own endpoint. Return a non-2xx status and a compact JSON body. The model sees External tool "TOOL_NAME" failed: HTTP STATUS — followed by the first 500 characters of the body. Response headers such as Retry-After are dropped. Put class, retryAfterSeconds, and the first recovery step at the top of the body. A 2xx response that carries an error payload counts as a success and gets no errorType.
• To classify a third-party API you do not control, wrap the call in a flow tool. An api-call step with errorHandling: "continue" writes its defaultValue when the call fails, so set defaultValue to a structured error object, and add a transform-data step that gives success and failure one result shape. If the step has a responseMapping, the mapping also applies to defaultValue, so map the error fields too. The step cannot read the upstream status, so the fallback object carries one fixed class. A custom tool has no network egress unless it opts in with networkAccess (and secrets for credentials); then it can make the call and shape the failure class itself.
• For an MCP server tool, put the class and recovery steps in the content text. Runtype passes the content of a tools/call result to the model and does not read isError, so a result with isError: true is recorded as a successful call. A non-2xx HTTP response or a JSON-RPC error is still reported as a failed call.
• external tool calls time out after 30 seconds, and the model receives a timeout error. For slower upstreams, use a detached subagent tool (see tool-design-execution).

Errors Runtype writes for you

Tell the agent, in its instructions, how to handle the errors that Runtype writes itself:

• A tool call that the user denied at approval. It cannot be retried.
• A call interrupted mid-run on a resumed turn. Its effects are unknown, so the agent must check whether the write happened before it retries. Set idempotent: true on read-only runtime tools so that Runtype can safely run an interrupted call again. MCP tools follow the server's readOnlyHint and idempotentHint annotations.
• Missing secrets or an MCP server that is not configured (not_configured). The agent cannot fix these. It should tell the user what to set up.

For MCP servers that use OAuth2, Runtype refreshes an expired token and retries once after a 401. Use authRequired only when the user must act. For an MCP server, have the recovery step tell the user to reconnect the server from Tools.

Confirmation requests on chat surfaces

Behind a Persona widget, expose the built-in local tools (features.askUserQuestion.expose, features.suggestReplies.expose). An ambiguous match then becomes a rendered choice that the user taps, not a JSON options list that the model has to narrate. Elsewhere, return the options in the tool result as shown above.

Flow step defaults

Some flow steps continue when they fail. This partial list shows the behavior when errorHandling is unset:

• fetch-url, api-call, crawl, search, and transform-data continue and write defaultValue.
• paginate-api fails the step.
• upsert-record reports success: false and writes no output when its source variable is missing or does not resolve to a JSON object. update-record does the same when it cannot find the target record. Both continue with defaultValue on other failures.
• A tool-call step ignores errorHandling. It uses config.onError, which fails the step by default. With onError: "continue", it writes { error, result: null }.

Set errorHandling to "fail" or "continue" explicitly on any step where a silent continue would hide a real failure from the agent.

Pauses and retries

• The platform's own pauses are not errors. An await event means the run is waiting on a person or the client: an approval, a client tool, an elicitation, or a detached run. Its awaitReason separates pauses that resume on their own from pauses that the client must resolve. A surface must render them as pauses, not as failures.
• The model retries failed tools, not the platform. retryAfterSeconds in the result is what stops a tight loop. Also set the agent's Max turns and Cost budget (USD) so that a tool that keeps failing cannot loop without limit.
• Test failure paths with execute_tool and deliberately wrong inputs before you attach the tool to an agent. Capture real failures as eval cases with add_eval_case_from_execution so that the fix stays pinned.

See also Agent tools: Error handling, Runtime tools: Tool replay after an interrupted turn, and Runtime tools: Pause and resume on an agent dispatch.