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.
npx agentmods add skills/synaptiai/agent-capability-standard/delegatenpx skills add synaptiai/agent-capability-standard --skill delegategit clone --depth 1 https://github.com/synaptiai/agent-capability-standardWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00033 | $0.02736 |
| Opus 5 | $0.00016 | $0.01368 |
| Sonnet 5 | $0.00007 | $0.00547 |
| Haiku 4.5 | $0.00003 | $0.00274 |
Grade A, and why
delegate 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 3d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Intent
Delegate a complex task to one or more subagents by defining clear contracts, input/output interfaces, and strategies for merging results. Ensure coordinated execution with conflict resolution.
Success criteria:
- Task decomposed into delegatable subtasks
- Each subtask has explicit contract (inputs, outputs, constraints)
- Interface between tasks is well-defined
- Merge strategy handles conflicts and failures
- Dependencies between subtasks are clear
Compatible schemas:
schemas/output_schema.yaml
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
task |
Yes | string or object | The overall task to delegate |
agents |
No | array | Available agents/workers for delegation |
constraints |
No | object | Global constraints (timeout, resource limits) |
merge_strategy |
No | string | How to combine results (first_wins, consensus, aggregate) |
failure_policy |
No | string | What to do on subtask failure (abort, continue, retry) |
Procedure
-
Analyze task: Understand the overall objective
- Identify the goal and success criteria
- Determine if task is parallelizable
- Identify shared state or resources
- Assess complexity and scope
-
Decompose into subtasks: Break into delegatable units
- Each subtask should be independently executable
- Minimize dependencies between subtasks
- Identify natural parallelization boundaries
- Use
decomposecapability patterns
-
Define contracts: Specify expectations for each subtask
- Input: what data/context each subtask receives
- Output: what each subtask must produce
- Constraints: limits on time, resources, scope
- Verification: how to check subtask completion
-
Design interfaces: Specify data flow between subtasks
- Format of inputs and outputs
- Required fields and optional extensions
- Error formats and status codes
- Handoff protocols
-
Plan merge strategy: How to combine results
- Handle successful completions
- Resolve conflicts between subtask outputs
- Aggregate partial results
- Determine final output format
What ships with it
2 files 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.
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.
- 3d ago First seen · 386 lines · 33 tokens per session scan A 73cae0dff7fd
delegate is a skill published in the GitHub repository synaptiai/agent-capability-standard (4 stars, last pushed 3d ago), licensed Apache-2.0. It adds 33 tokens to every session and 2,736 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
employment-contract-templates
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
rag-implementation
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
hugging-face-dataset-creator
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, and streaming row updates. Designed to work alongside HF MCP server for comprehensive dataset workflows.
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
calendar-event-create
Create a Google Calendar event with title, time, and attendees.
file-read
Read a file from an allowed path on the local filesystem.