Tool Output Design

SkillFiles & storage

Design or audit what an agent tool returns: shape and trim payloads, paginate, report partial success, reference files and media, and add next-step hints. Use when tool output bloats the context window.

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Also: Claude Code · Cursor · Codex

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Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

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Tool Output DesignStart free

What this skill tells your AI

The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/runtypelabs/skills/skills/tool-design-output/SKILL.md and read by ahel’s review.

Every byte a tool returns costs context tokens and becomes part of the model's next input. Design the result as that input.

Procedure

  1. List what the agent needs to decide its next step. Only those fields are essential. Everything else is optional detail or a follow-up call.
  2. Define a flat, named shape for the result and keep it identical across calls.
  3. Decide the size policy: default summary, expansion flags, cursor pagination, truncation limits, and references for blobs.
  4. Add navigation: hasMore and cursor, GUI URLs, and a next-action hint.
  5. Handle mixed outcomes with per-item status for anything that touches more than one item.
  6. Verify. Run the tool once and read the raw result. Then run the agent and check how much of its context the tool results take. If they dominate, tighten the size policy.

Rules with examples

Shape the response (Response Shaper)

Never return the upstream payload as-is. Flatten nesting, select relevant fields, rename cryptic keys, add computed fields, and convert machine encodings to readable ones (ISO-8601 datetimes, not epoch seconds; active: true, not status_code: 2).

Before:

{
  "data": {
    "id": "usr_123",
    "user": {
      "attributes": {
        "first_name": "Ada",
        "last_name": "Lovelace",
        "contact": { "primary_email": "ada@example.com" },
        "perm": { "r": "admin" },
        "st": 2,
        "created": 1719800000
      }
    }
  }
}

After:

{
  "id": "usr_123",
  "name": "Ada Lovelace",
  "email": "ada@example.com",
  "role": "admin",
  "active": true,
  "createdAt": "2024-07-01T02:13:20Z"
}

Spend tokens deliberately (Token-Efficient Response)

  • Essential fields only. Codes over prose where a code is unambiguous.
  • Truncate long text fields at a documented length and say so ("bodyTruncated": true).
  • Count instead of listing when the agent needs the number, not the items.
  • Make the expensive part opt-in: includeBody: false by default, with the description telling the agent which call fetches the full item.
  • Log response sizes so oversize results show up in traces.

Paginate by cursor (Paginated Result)

Page numbers and offsets drift as data changes. A cursor that encodes the last item's sort key, not a position, does not. Return:

{
  "items": [],
  "count": 50,
  "hasMore": true,
  "nextCursor": "eyJhZnRlciI6ImN0Y18wNTAifQ",
  "nextAction": { "tool": "list_contacts", "args": { "cursor": "eyJhZnRlciI6ImN0Y18wNTAifQ" } }
}

Accept limit with a sensible default and a hard maximum. Keep ordering stable for the same query. Always include hasMore explicitly, even when false.

Summary first, detail on request (Progressive Detail)

Default to the summary the agent usually needs. Offer a detail enum (summary | full) or specific include* flags for sections such as comments or attachments, and document exactly what each level includes. Pair with a get_* tool that returns one item in full.

Say what to do next (Next-Action Hint)

A result can carry the suggested follow-up: tool name plus the parameters to pass, the data still required, and alternative paths. This is the tool-side half of dependency hints and removes a guess from the agent's loop.

{
  "jobId": "job_9",
  "status": "queued",
  "nextAction": { "tool": "check_job_status", "args": { "jobId": "job_9" }, "afterSeconds": 30 }
}

Link to the interface (GUI URL)

Any tool that creates or reads a resource with a web UI returns viewUrl, and editUrl where editing exists. Use deep links to the specific resource. Note expiry for links to sensitive resources.

Report mixed outcomes per item (Partial Success)

Batch and multi-source tools never collapse to a single boolean. Return successes, failures with reasons, summary counts, and a retry hint for exactly the failed items:

{
  "total": 3,
  "succeeded": 2,
  "failed": 1,
  "results": [
    { "email": "a@example.com", "ok": true },
    { "email": "b@example.com", "ok": true },
    { "email": "c@example.com", "ok": false, "error": "mailbox full", "retryable": true }
  ],
  "nextAction": { "tool": "send_invites", "args": { "emails": ["c@example.com"] } }
}

Reference large data instead of embedding it (Resource Reference)

Files and blobs travel as typed URIs (resource://files/abc, with contentType, sizeBytes, and a name) that other tools resolve. The conversation carries the reference, not the bytes. Handle expired or missing references with a clear error.

One vocabulary across the set (Canonical Tool Model)

Define canonical shapes (User, Task, Event, Page) once and map every tool's upstream response onto them. Same field names for the same concept everywhere (createdAt in every tool, never created, creationDate, and ts in three tools). Consistent shapes are what let one tool's output feed the next tool's input without a transformation step in the agent's head.

Anti-patterns

  • Returning response.json() from the upstream API.
  • An unbounded array with no limit, no cursor, and no count.
  • hasMore omitted when false, so the agent cannot tell "done" from "unknown".
  • A batch tool that throws on the first failure and discards the successes.
  • Different tools naming the same field differently.
  • Embedding a 200 KB document body in a result the agent only needed the title from.

For error shapes, retry classification, and step failure defaults, see tool-design-errors.

On Runtype

  • Runtime tool results go to the model directly. An external tool returns the upstream body unchanged (its body template maps the request, not the response), so shape a noisy payload in a flow tool whose api-call step feeds a transform-data step. A custom code tool has no network egress unless it opts in with networkAccess (an allowedHostnames list is the safe form); without it, the tool can shape only what arrives in its parameters.

  • A flow tool returns the value that the flow's final executed step wrote. Set outputVariable to return one named flow variable instead, such as the transform-data output, and outputMapping to select a dot path inside it. A _-prefixed variable is rejected, and a variable the flow never assigned fails the tool call. See Flow tools.

  • If you run your own MCP server, apply these rules to its results. You cannot reshape a third-party MCP server's results, so prefer its narrower tools.

  • paginate-api is the platform's pagination step for upstream lists (cursor, offset, page, or Link header).

  • Empty is not the same as failed. A fetch-class step (fetch-url, api-call, crawl, search) with errorHandling unset swallows a failure into defaultValue (or an empty result) and reports success, so a downstream transform-data or upsert-record runs over zero rows as if the API returned nothing. validate_flow warns with FETCH_CLASS_SWALLOWING_FEED; set errorHandling: { "onError": "fail" } when an empty result must not look like a real one. Unlike these steps, paginate-api fails by default.

  • upsert-record needs a JSON object as its source. validate_flow warns with UPSERT_RECORD_SOURCE_NOT_JSON when a text prompt feeds it, and the write fails at runtime. Set the prompt's responseFormat to "json", shape the value in transform-data, or set contentField on the upsert step to wrap the string.

  • Store large content in a record and return its id. The agent calls get_record to fetch it.

  • Binary media over 4 KB in a tool result, such as a screenshot or a generated image, becomes a runtype-asset:// handle automatically, so later turns carry the handle, not the bytes. Handles expire after 7 days. To accept one, declare the parameter with contentEncoding: "base64", and Runtype substitutes the stored bytes before the call:

    { "image": { "type": "string", "contentEncoding": "base64" } }
    
  • The model receives each new tool result in full; Runtype does not truncate it for you. Older results outside the recent window (40,000 tokens by default) are masked: the model sees only a short "cleared" placeholder, not a trimmed copy. Write anything the agent needs in later turns to a record. See Context compaction.

  • To verify a result shape, run the tool with execute_tool and read the raw result. After an agent run, the Context window bar in Logs shows the share of input tokens that tool results take, and hints when they dominate.

Signals

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Item type
skill
Key
tool-design-output
Source
github.com/hashgraph-online/awesome-codex-plugins