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/hraness/direct/phase-orchestratornpx skills add hraness/direct --skill phase-orchestratorgit clone --depth 1 https://github.com/hraness/directWhat 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 | $0.00101 | $0.04842 |
| Opus 5 | $0.00051 | $0.02421 |
| Sonnet 5 | $0.00020 | $0.00968 |
| Haiku 4.5 | $0.00010 | $0.00484 |
Grade A, and why
phase-orchestrator 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 2d 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.
This is a copy
100% identical to phase-orchestrator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 498 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase Orchestrator
Goal
Run a phase-based plan through a repeatable delegated workflow. The plan is the source of truth, any PRD/spec is supporting context, and each phase should move through orientation, implementation, validation, review, plan updates, and commits by default.
Use this skill only when the user explicitly asks for delegated phase orchestration, invokes this skill, or asks to implement a plan/checklist using subagents.
Companion Skills
This skill is the parent of a five-skill workflow:
write-phase-plan— authors plans in the format this skill consumes best.phase-implementer— the delegated worker contract for implementing exactly one phase (Phase Loop step 2).phase-reviewer— the delegated worker contract for the review-and-fix pass on a completed phase (Phase Loop step 4).phase-final-reviewer— the delegated worker contract for the end-to-end review of the whole feature after all phases (Final Whole-Feature Pass).
Each worker skill carries that role's standing rules: single-phase or single-pass scope, no-revert discipline, no-commit default, and the required final-response format. The parent's prompt only needs to supply the per-run context from the templates below.
How to dispatch a worker role depends on the host:
- Named custom agents. If the host supports named custom agents or subagent types (Cursor custom agents, for example), prefer a dedicated agent per role whose definition is the matching companion skill's body.
- General subagent + installed skill. Otherwise, launch a general-purpose subagent and instruct it to load and follow the matching installed companion skill by name.
- Inline rules. If the subagent cannot load skills, paste the companion skill's standing rules into the prompt along with the per-run context.
Host Mapping
- Use the host's todo tracker (
TodoWritein Cursor) for the in-chat orchestration state. Keep exactly one phase or orchestration stepin_progress. - Use the host's subagent or task tool (
Subagentin Cursor) for delegated implementation, broad read-only exploration, review/fix passes, validation, and shell/git work when delegation is useful. - Use fast read-only subagents (Cursor's
exploretype, where available) for broad codebase discovery before implementation. - Use shell-focused subagents only for command-heavy validation or git operations.
- Respect the user's or host's model choice for workers. Pass a model explicitly only when the user requests a specific model for the run or for a specific worker.
- Use background subagents when the host supports them and independent read-only investigations can run in parallel.
- Do not assume subagents can be "closed"; inspect their final response and continue from the parent agent.
- Record every spawned subagent's ID in the main thread (alongside its phase
in the todo/phase notes) when the host exposes one. Some hosts can resume a
completed subagent by ID with its full context preserved (Cursor's task
tool
resumeparameter). The user may ask for flows that reuse the same agent across the run — the same reviewer re-checking its own earlier findings, or an implementer revisiting its phase after review — and resuming beats a fresh dispatch there because the agent keeps everything it already learned. Keeping the IDs in thread history is what makes that possible later. - Treat worker responses as structured handoffs. Require the result fields defined below so the parent can compare and combine results without carrying an unstructured transcript in context.
- Follow the host's normal tool rules: read tool schemas before unfamiliar calls, avoid destructive git commands, and never revert user-owned work.
What ships with it
4 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.
- 2d ago First seen · 498 lines · 101 tokens per session scan A 14d332015ddd
phase-orchestrator is a skill published in the GitHub repository hraness/direct (2 stars, last pushed 2d ago), licensed MIT. It adds 101 tokens to every session and 4,842 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to phase-orchestrator, differing in 0 lines, and is treated as a copy.
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