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 skills add jstoup111/ai-conductor --skill conductgit clone --depth 1 https://github.com/jstoup111/ai-conductorWrote 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/jstoup111/ai-conductor/conduct)<a href="https://agentmods.dev/skills/jstoup111/ai-conductor/conduct"><img src="https://agentmods.dev/badge/skills/jstoup111/ai-conductor/conduct.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.05614 |
| Opus 5 | $0.00018 | $0.02807 |
| Sonnet 5 | $0.00007 | $0.01123 |
| Haiku 4.5 | $0.00004 | $0.00561 |
Grade A, and why
conduct 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 — 380 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Walks a feature through the complete SDLC flow by checking artifact state and directing the user
to the correct next skill. Run the conduct workflow at any point to see where you are and what
to do next (Claude /conduct; Codex $conduct).
Does NOT run other skills internally — it assesses state and directs. The user invokes each skill.
Session Model
Fresh LLM session per executed step. Every step — design through finish —
starts without prior-step conversational context and reads its inputs from the
persisted artifacts. The session ID/marker under .pipeline/ supports the
current step only; it is reset at the next step boundary.
- Design phase (bootstrap → plan): Each step reads the approved artifact produced by its predecessor.
- Build phase (pipeline): The conductor drives the task loop. The selected host agent orchestrates each task by dispatching subagents. Subagent context is isolated and discarded — only a ~2-3 line summary returns to the orchestrator per task. No context compaction needed.
- Ship phase (manual-test → finish): Lightweight steps, context stays bounded.
Retries within the same step resume that step's session so partial work and failure context are retained. A later step never resumes it. With per-step provider routing, session identity is additionally provider-local: another provider starts fresh, and only a same-step retry on the same provider resumes.
The Flow
Step 1: /bootstrap → UNDERSTAND
Step 2: /memory → UNDERSTAND
Step 2.5: /assess → UNDERSTAND (existing projects only — skipped for new)
Step 3: /explore → DECIDE (context, approaches, + decide product/technical TRACK)
Step 4: Complexity Assessment → DECIDE (classify S/M/L, determines which steps run)
Step 5: Worktree setup → DECIDE (create feature branch + worktree — all subsequent commits are isolated)
Step 6: /prd → DECIDE (product-only PRD; PRODUCT track only — skipped on technical)
Step 7: /architecture-diagram → DECIDE (generate/update current-state diagrams; skipped for Small)
Step 7b: /architecture-review → DECIDE (skipped for Small, lightweight for Medium — produces ADRs; precedes stories)
Step 8: /stories → DECIDE (from PRD FRs on product; technical stories on technical)
Step 9: /conflict-check → DECIDE (skipped for Small; root-routes kickback → prd|architecture|stories)
Step 10: /plan → DECIDE (technical implementation plan, grounded in the architecture + stories)
Step 10b: /coherence-check → DECIDE (Medium/Large traceability gate after plan)
Step 11: /writing-system-tests → BUILD (skipped for Small)
Step 12: /pipeline or /tdd → BUILD (pipeline evaluator satisfies code-review gate)
Step 13: Engine-native configured-verifier gate → BUILD (repository-configured aggregate verification)
── CHECKPOINT ── → User reviews build output, can go back or continue
Step 14: /manual-test → SHIP (validate stories, bug loop via /tdd — auto-skip for non-endpoint features)
── CHECKPOINT ── → User reviews test results, can go back or continue
Step 15: /prd-audit → SHIP (PRODUCT track only — audit shipped impl vs PRD FRs; GATE; skipped on technical)
Step 16: /architecture-review --as-built → SHIP (shipped code vs APPROVED ADRs; GATE — BLOCKED on an ADR violation)
Step 17: /finish → SHIP (verify, review changes, present options, and commit the durable shipped record before completion)
What ships with it
1 file 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.
- yesterday Changed · +3 lines 4b3e27c9f8a0
- 7d ago First seen · 377 lines · 36 tokens per session scan A 0fb10b91d679
conduct is a skill published in the GitHub repository jstoup111/ai-conductor (7 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 5,614 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 2026-08-31.
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