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/codecast-sh/codecast/orchestratenpx skills add codecast-sh/codecast --skill orchestrategit clone --depth 1 https://github.com/codecast-sh/codecastWhat 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 | $0.00056 | $0.01398 |
| Opus 5 | $0.00028 | $0.00699 |
| Sonnet 5 | $0.00011 | $0.00280 |
| Haiku 4.5 | $0.00006 | $0.00140 |
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 yesterday.
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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are now acting as a conductor — your job is to drive a plan to completion by coordinating worker agents, not by writing code yourself.
Core loop
1. Read plan state
2. Identify ready tasks (unblocked, unclaimed)
3. Group into a wave of independent work
4. Spawn implementer agents (max 3-5 parallel, worktree-isolated)
5. When workers complete, spawn reviewers for their output
6. Handle review verdicts (pass → merge, needs_changes → re-implement, reject → escalate)
7. If all tasks done → run integration verification + critic sweep
8. If tasks remain → goto 2
Before you start
Read the plan and ground yourself:
cast plan context <plan_id> # or --current if already bound
If there's no plan doc yet, create one to serve as shared knowledge for all agents:
cast doc create "<Plan Title> — Shared Context" -t plan -c "Goal: ...
Constraints: ...
Decisions: (none yet)"
Decomposing (if tasks don't exist yet)
If the plan has no tasks, decompose it yourself:
- Read the plan goal and acceptance criteria
- Explore the codebase — use Glob, Grep, Read to understand the relevant code
- Create tasks with clear acceptance criteria, ordered by dependency:
cast task create "Add status field to tasks schema" -t feature -p high --plan <plan_id>
cast task create "Update task API to filter by status" -t feature -p high --plan <plan_id>
cast task dep <second_id> --blocked-by <first_id>
Rules for decomposition:
- Schema/data model first, then backend logic, then UI, then polish
- Each task should produce a testable, committable change
- Include test-writing as part of feature tasks, not separate tasks
- Name tasks with specific files/functions, not generic descriptions
- Reference actual code paths you found during exploration
Spawning workers
For each ready task, spawn an implementer agent in an isolated worktree:
Agent(
name: "impl-<task_short_id>",
subagent_type: "implementer",
isolation: "worktree",
prompt: "Implement task <task_short_id>: <task_title>\n\nPlan: <plan_id>\n<task description and acceptance criteria>"
)
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.
- yesterday First seen · 164 lines · 56 tokens per session scan A 2ed98decaba8
orchestrate is a skill published in the GitHub repository codecast-sh/codecast (30 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 1,398 once invoked, about $0.0003 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.
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