Agent skill

Tool Design Output

by hashgraph-online in hashgraph-online/awesome-codex-plugins

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.

Apache-2.0Auto-check passedAgent Workflows

Install Tool Design Output

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill tool-design-output -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins tool-design-output --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/runtypelabs/skills/skills/tool-design-output .claude/skills/tool-design-output && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tool-design-output
GitHub stars
1.3k
Token cost
~2.3k tokens
SKILL.md length
1,118 words
Files
2
Skills in repo
714
Repo updated
First seen
Licence
Apache-2.0

At a glance

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.

  • Works in 6 steps: List what the agent needs to decide its… → Define a flat, named shape for the… → Decide the size policy: default summary,… → …
  • Tool output bloats the context window
  • SKILL.md covers Procedure, Rules with examples, Anti-patterns and On Runtype
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tool Design Output is an agent skill from hashgraph-online/awesome-codex-plugins. 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.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Agent Workflows, covering Context engineering. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.

When your agent uses it

  • Tool output bloats the context window
  • Tasks that involve Context engineering

Example prompts

  • “/tool-design-output”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. List what the agent needs to decide its next step. Only those fields are
  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,
  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
  6. Verify. Run the tool once and read the raw result. Then run the agent and check how

What it can do on your machine

Read from SKILL.md and the folder at commit 9e7b281. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.runtype.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tool Design Output loads about 2.3k tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 1,118 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 9e7b281, republished under its Apache-2.0 licence (© hashgraph-online). 1,118 words, ~2,293 tokens.

Download SKILL.mdSave it as .claude/skills/tool-design-output/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
tool-design-output
description
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.
user-invocable
true
argument-hint
[tool whose result shape to design]

Tool Output Design

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:

json
{
  "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:

json
{
  "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:

json
{
  "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.

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

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:

json
{
  "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.

Show full SKILL.md (460 more words)Show less

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:

    json
    { "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.

© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/runtypelabs/skills/skills/tool-design-output of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 9e7b281

Compare with similar skills

Tool Design Output next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tool Design Output compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tool Design Output this skillhashgraph-online/awesome-codex-plugins1.3k—~2.3kAutomated safety check: PassApache-2.0
Context Mode Output Sandboxmksglu/context-mode26k—~4.1kAutomated safety check: PassCustom licence
Memori Long-Term MemoryMemoriLabs/Memori17k—~2kAutomated safety check: NotesCustom licence
Picoclaw Skill Creatorsipeed/picoclaw30k—~4.4kAutomated safety check: PassMIT
ccc Semantic Code Searchcocoindex-io/cocoindex-code2.8k—~938Automated safety check: PassApache-2.0
Context Mode for Antigravity CLImksglu/context-mode26k—~850Automated safety check: PassCustom licence

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Categories

Questions about Tool Design Output

What does Tool Design Output do?

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. Tool Design Output is an agent skill from hashgraph-online/awesome-codex-plugins. 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.

When should I use Tool Design Output?

Tool Design Output fits situations like: tool output bloats the context window; tasks that involve Context engineering.

How do I install Tool Design Output in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill tool-design-output -a claude-code`. Or copy the skill folder (plugins/runtypelabs/skills/skills/tool-design-output in hashgraph-online/awesome-codex-plugins) into .claude/skills/tool-design-output in your project. Claude Code loads it when a task matches its description.

How do I install Tool Design Output in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill tool-design-output -a codex`. Or copy the skill folder (plugins/runtypelabs/skills/skills/tool-design-output in hashgraph-online/awesome-codex-plugins) into .agents/skills/tool-design-output in your project. Codex loads it when a task matches its description.

Can I use Tool Design Output in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill tool-design-output -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tool-design-output, .gemini/skills/tool-design-output, .github/skills/tool-design-output and .opencode/skills/tool-design-output in your project.

What does Tool Design Output need to run?

SKILL.md names no scripts, command-line tools or credentials: Tool Design Output is instructions for the agent only.

Does Tool Design Output access the network?

SKILL.md names 1 domain. As links in the text: docs.runtype.com. This is read from the text; nothing was executed.

Is Tool Design Output safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tool Design Output use?

Tool Design Output is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tool Design Output use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tool Design Output?

Skills that share tags, products or a category with Tool Design Output: Context Mode Output Sandbox (mksglu/context-mode, 26k stars), Memori Long-Term Memory (MemoriLabs/Memori, 17k stars), Picoclaw Skill Creator (sipeed/picoclaw, 30k stars) and ccc Semantic Code Search (cocoindex-io/cocoindex-code, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tool Design Output?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,255 GitHub stars. The repository holds 714 skills in this directory. The repository was last updated on October 9, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.