agents_guide

agents_guide is a skill for Claude Code, Codex from siddsachar/row-bot. It costs 15 tokens per session (1,549 once invoked), scanned A, original, Apache-2.0.

A guide for deciding when to delegate focused work to child agents, which are separate assistants handling bounded parts of a larger task.

In plain words
What is it for?
Use it when several substantial workstreams can run independently, when specialist review is useful, or when implementation and testing should be separated.
Why use it?
It helps divide independent research, planning, writing, review, or testing work without losing control of the main task.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it when several substantial workstreams can run independently, when specialist review is useful, or when implementation and testing should be separated.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/siddsachar/row-bot/agents_guide
About the project

Row-Bot is a local-first desktop AI assistant that combines language models with memory and tools for working across files, repositories, workflows, and communication channels. It is intended for people who want an assistant that can run locally while keeping application data on their machine.

siddsachar/row-bot · 1,632 stars · on GitHub · row-bot.ai

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.

Any agent
npx skills add siddsachar/row-bot --skill agents_guide
Clone the repo
git clone --depth 1 https://github.com/siddsachar/row-bot

Made for: Claude Code, Codex.

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 agents_guide

README.md
[![agentmods](https://agentmods.dev/badge/skills/siddsachar/row-bot/agents_guide/github.svg)](https://agentmods.dev/skills/siddsachar/row-bot/agents_guide)
Your own site
<a href="https://agentmods.dev/skills/siddsachar/row-bot/agents_guide"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/agents_guide/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agents_guide

Your own site · 80×15
<a href="https://agentmods.dev/skills/siddsachar/row-bot/agents_guide"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/agents_guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00015 $0.01549
Opus 5.5 $0.00006 $0.00620
Sonnet 5.5 $0.00003 $0.00310
Haiku 4.5 $0.00002 $0.00155

Measured 1mo ago against content hash 9e6adf88edd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agents_guide 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 1mo 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.

tool_guides/agents_guide/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS:

  • Delegate automatically when two or more substantial workstreams can proceed independently, a bounded specialist review/research task protects parent context, comparison needs independent evidence, a long goal benefits from implementation/review/test roles, or write work can be isolated safely in Worktrees.
  • Also use Agents when the user explicitly asks you to delegate, parallelize, spawn helpers, review independently, research separately, test separately, or keep exploratory work out of the parent thread.
  • Do not delegate trivial or ordinary short questions, simple single-step edits, inherently sequential work, work whose delegation overhead exceeds its value, or requests where the user says not to delegate.
  • Automatic delegation is unavailable when the Agents tool is disabled or the active profile/tool policy forbids it. Do not try to work around that boundary.
  • Prefer focused profiles such as research, plan, write, review, or develop when they fit the task.
  • Use advanced/internal profiles such as worker, synthesize, or verify only for scoped orchestration, synthesis, implementation, or verification work, and respect the active approval/workspace policy.

DELEGATING:

  • Call delegate_work with a precise objective, a focused context packet, and a profile when useful.
  • Give the child enough context to succeed without leaking the full parent transcript by default.
  • Use the smallest useful wave and avoid duplicate objectives. Start ordinary automatic children with delegate_work(wait=false, required=true).
  • After an asynchronous start, continue useful independent work and stream a natural concise update while the children run. The parent may use other tools or create another child wave.
  • Before finalizing, call agent_wait(orchestration_id=...) to join the current required cohort and incorporate its ordered results. If you create a later wave, group-wait again before finalizing.
  • delegate_work(wait=false) defaults to required automatic orchestration unless you explicitly set required=false; the parent thread stays responsive while the durable barrier waits.
  • Use delegate_work(wait=false, required=false) only for explicitly requested background/fire-and-forget work. Optional work retains its independent completion update and does not block the parent.
  • Do not loop on agent_status or narrate each required child completion. Use status only for explicit inspection and use the group wait for the barrier.
  • Use wait=true only when the user explicitly asks you to block on one child before answering.
  • Each automatic child inherits the parent model. Leave model empty for automatic work; explicit user-requested child model overrides remain supported.
  • For independent parallel writers, create separate existing folders first and pass a distinct developer_workspace_path to each delegate_work call. Changing shell CWD alone does not change Agent workspace locking, and children assigned to the same folder still serialize.
  • Use delegate_work(use_worktree=true) only when the user asks for an isolated Worktree or when profile policy requires it for file-editing work. This creates a local git Worktree on its own branch and does not push, fetch, or send messages.
  • For natural child-agent model requests like "use gpt5.5 via codex" or "use qwen 3.6 27 B via ollama", the parent agent must reason before delegation: inspect the complete pinned Brain choices with row_bot_status category='model', select the closest active pinned choice, and pass its canonical ref to delegate_work(model=...). Leave model empty when the child should inherit the parent model. Do not pass raw natural phrases or unpinned provider refs.
  • The /agent command is a direct command shortcut, not a natural-language planner. When a user explicitly types /agent --model=model:provider:model-id ..., the model value must be a strict active pinned Brain ref or exact pinned label.
  • Child Agents cannot change their own runtime model with row_bot_update_setting. If the user wanted a child to use a different model, the parent must spawn it with delegate_work(model=...) or the user must use /agent --model=....
  • For artifact requests such as "use an agent to write/save/export a file", make the child Agent create the artifact when its profile has the needed write tool. Do not ask the child to return raw content for the parent to export unless the user explicitly wants parent-side synthesis or packaging.
  • A review, critique, or edit Agent must receive the complete material it is reviewing: include the complete draft in context, or include a concrete workspace-relative artifact path plus the review criteria. Never launch a reviewer against a draft that does not exist yet.
  • When the parent will draft the material, finish the draft before delegating the reviewer. When a child drafts it, use a real later wave: let the drafting child finish, then delegate the reviewer from the resumed parent with the returned draft or stable artifact path in context.
  • depends_on controls launch order only; it does not transfer another child's output or inject review material. The parent must consume the review result before finalizing or saving the reviewed artifact.
  • Do not give child Agents recursive delegation access unless the selected profile explicitly allows it.

Read the full file on GitHub · 58 lines

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. 1mo ago First seen · 58 lines · 15 tokens per session scan A 9e6adf88edd2

Subscribe to this mod's changes

agents_guide is a skill published in the GitHub repository siddsachar/row-bot (1,632 stars, last pushed today), licensed Apache-2.0. It adds 15 tokens to every session and 1,549 once invoked, about $0.0001 per session on Opus 5.5. 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.