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.
git clone --depth 1 https://github.com/boparaiamrit/skills-by-amritWrote 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.
[](https://agentmods.dev/commands/boparaiamrit/skills-by-amrit/orchestrate)<a href="https://agentmods.dev/commands/boparaiamrit/skills-by-amrit/orchestrate"><img src="https://agentmods.dev/badge/commands/boparaiamrit/skills-by-amrit/orchestrate/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.
<a href="https://agentmods.dev/commands/boparaiamrit/skills-by-amrit/orchestrate"><img src="https://agentmods.dev/badge/commands/boparaiamrit/skills-by-amrit/orchestrate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.01292 |
| Opus 5 | $0.00010 | $0.00646 |
| Sonnet 5 | $0.00004 | $0.00258 |
| Haiku 4.5 | $0.00002 | $0.00129 |
Grade A, and why
orchestrate 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 10d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/orchestrate — Agent Chain Orchestration
Chain multiple specialist agents in sequence with structured handoff documents. Each agent builds on the previous agent's output.
Predefined Chains
| Chain | Agents | Use Case |
|---|---|---|
feature |
researcher → planner → executor → reviewer → verifier | New feature implementation |
bugfix |
debugger → planner → executor → verifier | Bug investigation and fix |
refactor |
mapper → planner → executor → reviewer | Code restructuring |
security |
mapper → investigator → reviewer | Security assessment |
Instructions
Step 1: Parse Arguments
From $ARGUMENTS, extract:
- Chain:
feature,bugfix,refactor, orsecurity - Task description: What needs to be done
If no chain specified, infer from the task description:
- Bug/error/fix keywords →
bugfix - Refactor/restructure/reorganize →
refactor - Security/vulnerability/audit →
security - Everything else →
feature
Step 2: Initialize Orchestration
mkdir -p .planning/orchestration
Create .planning/orchestration/[task-slug]-chain.md:
# Orchestration: [task description]
**Chain:** [chain type]
**Agents:** [agent1] → [agent2] → [agent3] → ...
**Started:** [ISO timestamp]
**Status:** In Progress
## Handoffs
[Will be populated as agents complete]
Step 3: Execute Agent Chain
For each agent in the chain:
3a: Brief the Agent
Provide the agent with:
- The original task description
- The handoff document from the previous agent (if any)
- The agent's specific role and expected output
3b: Run the Agent
Spawn the agent as a subagent using Task:
Researcher Agent:
- Investigate the codebase, dependencies, existing patterns
- Output: Research findings, relevant files, constraints identified
Planner Agent:
- Create an implementation plan based on research
- Output: Task breakdown, file changes, acceptance criteria
Executor Agent:
- Implement the plan
- Output: Files modified, implementation summary
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.
- 10d ago First seen · 196 lines · 19 tokens per session scan A eb684a2906e0
orchestrate is a command published in the GitHub repository boparaiamrit/skills-by-amrit (5 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 1,292 once invoked, about $0.0001 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.