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/firstp1ck/pi-coding-agent-forge/research-orchestrationnpx skills add Firstp1ck/pi-coding-agent-forge --skill research-orchestrationgit clone --depth 1 https://github.com/Firstp1ck/pi-coding-agent-forgeWrote 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/skills/firstp1ck/pi-coding-agent-forge/research-orchestration)<a href="https://agentmods.dev/skills/firstp1ck/pi-coding-agent-forge/research-orchestration"><img src="https://agentmods.dev/badge/skills/firstp1ck/pi-coding-agent-forge/research-orchestration.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00788 |
| Opus 5 | $0.00021 | $0.00394 |
| Sonnet 5 | $0.00008 | $0.00158 |
| Haiku 4.5 | $0.00004 | $0.00079 |
Grade A, and why
research-orchestration 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 5d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research orchestration
Single workflow entry point for end-to-end investigations. Detailed rules live in workspace-researcher/AGENTS.md (task class, parallel investigation, Deep Research Protocol, citation audit); this skill is the ordered checklist for executing them.
When to use
- Broad question with several independent sub-questions or claim clusters.
- Mixed sources (web + docs + papers) and one final report or contract output.
- User or delegating agent asked for deep research without pointing at a single comparison or single paper.
Prefer tech-deep-dive, competitor-analysis, or paper-summarizer when the task clearly matches one of those shapes.
Pipeline
- Classify depth — Quick / standard / deep (
AGENTS.mdtask-class table). Honor explicit quick / standard / deep or/deep-researchquick|standard|max when the user names them. Set expected tool budget. - Plan sub-questions — List facets and claims to verify; note which are high-stakes (citation audit mandatory). Prefer internal → official → web (
AGENTS.mddata source order) when gathering evidence. - Parallel pass — Batch
web_search/web_fetchper independent facet; optional subagents with tight scopes and structured handoff. - Merge — One synthesis pass; resolve contradictions; prefer primary sources.
- Gap closure — List unresolved material gaps; targeted follow-up searches or explicit “blocked” notes.
- Citation audit — For mandatory cases: every key finding → source row or
unsupported/inferential(AGENTS.md). - Deliver — Default report shape, contract JSON, or consumer-specific packet from
AGENTS.md; include Limitations and Research trace when depth is standard/deep or requested (APPEND_SYSTEM.md). - Log — Append a row to
workspace-researcher/MEMORY.md→ Research History (topic, task class, tool bucket, major gaps, notable sources).
Scout scripts → pipeline step
What ships with it
7 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.
- 5d ago First seen · 61 lines · 42 tokens per session scan A 9963241ebd15
research-orchestration is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (77 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 788 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 2026-08-30.
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