autosearch:delegate-subtask

autosearch:delegate-subtask is a skill for Claude Code, Codex from 0xmariowu/Autosearch. It costs 71 tokens per session (1,231 once invoked), scanned A, original, MIT.

An execution contract for giving a research sub-task to another agent or parallel session. It defines the question, scope, time and cost limits, expected evidence, and possible outcomes.

In plain words
What is it for?
Use it after breaking a larger question into smaller questions, so each one returns a status, short summary, and evidence list.
Why use it?
It makes split-off research tasks bounded and reviewable instead of leaving their inputs, limits, and results unclear.

Skill for Claude CodeCodex

Part of the autosearch plugin — 55 skills, 1 agent shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/0xmariowu/autosearch/delegate-subtask
Any agent
npx skills add 0xmariowu/Autosearch --skill delegate-subtask
Clone the repo
git clone --depth 1 https://github.com/0xmariowu/Autosearch

Made for: Claude Code, Codex.

Or install autosearch, the plugin that ships this one along with the rest of its 55 skills, 1 agent.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for autosearch:delegate-subtask

README.md
[![agentmods](https://agentmods.dev/badge/skills/0xmariowu/autosearch/delegate-subtask.svg)](https://agentmods.dev/skills/0xmariowu/autosearch/delegate-subtask)
Your own site
<a href="https://agentmods.dev/skills/0xmariowu/autosearch/delegate-subtask"><img src="https://agentmods.dev/badge/skills/0xmariowu/autosearch/delegate-subtask.svg" alt="Measured on agentmods" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,231 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01231
Opus 5 $0.00036 $0.00616
Sonnet 5 $0.00014 $0.00246
Haiku 4.5 $0.00007 $0.00123

Measured 5d ago against content hash e5b9ea007969, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

autosearch:delegate-subtask scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (__init__.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

autosearch/skills/meta/delegate-subtask/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Delegate Subtask — Execution Contract

decompose-task splits a problem into sub-questions. This skill says how to execute each sub-question with a stable, auditable contract: inputs, budget, outputs, failure modes. Borrowed from MiroThinker + DeepAgents + deer-flow + DeepResearchAgent subagent patterns.

Contract

input:
  id: str                     # stable subtask id, e.g. "sub_1" / "sub_1a"
  parent_id: str | null       # linking back to the decompose-task output
  question: str               # one specific sub-question
  rationale: str              # why this subtask matters for the parent goal
  scope: list[str]            # channels / tools the subtask may touch
  budget:
    latency_seconds: int
    cost_usd: float
    tool_calls: int           # max total tool invocations
  context_seed: list[dict]    # evidence already gathered the subtask should start with
  stop_conditions: list[str]  # e.g. "answer rubrics satisfied" / "budget exhausted"

output:
  id: str                     # echoes input.id
  status: "success" | "partial" | "failure"
  summary: str                # 3-6 sentences; what was found
  evidence: list[dict]        # slim-dict Evidence items the subtask produced
  citations: list[str]        # URL list, matched to evidence
  follow_ups: list[str]       # open questions, if partial
  metrics:
    latency_ms: int
    cost_usd: float
    tool_calls: int
    channels_hit: list[str]
  failure_reason: str | null

Invocation Policy

  • One subtask per thread/session — isolation matters. Do not merge two subtasks' tool calls into one session.
  • Budget is the governor. Subtask must halt when ANY budget axis is exhausted and report status: "partial".
  • Read context_seed, don't re-search it. Seed is evidence the parent already has; subtask should build on, not duplicate.
  • Return slim evidence — use autosearch's Evidence.to_slim_dict() shape so the parent can dedupe/merge.
  • Follow-ups are first-class. If a subtask runs out of budget but finds a promising lead, emit that in follow_ups for the parent planner to decide.

Read the full file on GitHub · 110 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 110 lines · 71 tokens per session scan A e5b9ea007969

Subscribe to this mod's changes

autosearch:delegate-subtask is a skill published in the GitHub repository 0xmariowu/Autosearch (44 stars, last pushed 29d ago), licensed MIT. It adds 71 tokens to every session and 1,231 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

sanity-best-practices

Sanity development best practices for schema design, GROQ queries, TypeGen, Visual Editing, images, Portable Text, Studio structure, localization, migrations, Sanity Functions, webhooks, Blueprints, and framework integrations such as Next.js, Nuxt, Astro, Remix, SvelteKit, Angular, Hydrogen, and the App SDK. Use this…

sanity-io/agent-toolkit · 164 tokens

portable-text-serialization

Render and serialize Portable Text to React, Svelte, Vue, Astro, HTML, Markdown, and plain text. Use when implementing Portable Text rendering in any frontend framework, building custom serializers for non-standard block types, converting Portable Text to HTML strings server-side, converting Portable Text to Markdown…

sanity-io/agent-toolkit · 85 tokens

video-perception

Use when the user mentions a video file (.mp4, .mov, .avi, .mkv, .webm), a YouTube URL, asks to watch/analyze/review a video, or references video content in conversation.

jordanrendric/claude-video-vision · 51 tokens

prior-art-search

Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification.

RobThePCGuy/Claude-Patent-Creator · 26 tokens

bigquery-patent-search

Fast, cloud-based patent searching across 100 million+ worldwide patents using Google BigQuery - keyword search, CPC classification, patent details retrieval.

RobThePCGuy/Claude-Patent-Creator · 34 tokens

development-assistant

Guides through adding new features, MCP tools, analyzers, and extending the patent creator system.

RobThePCGuy/Claude-Patent-Creator · 24 tokens