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dynamic-workflow 精选

Plan-in-code fan-outs, adversarial verification, waves.

在 GitHub 打开

安装方式

cp -r optional-skills/autonomous-ai-agents/dynamic-workflow ~/.claude/skills/dynamic-workflow

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/NousResearch/hermes-agent.git

依赖与权限

  • 无需 API Key
  • 需要联网访问外部服务
  • 依赖外部命令:git make
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
触发场景
A task is too big for one context window AND you can describe the split (per-file, per-endpoint, per-source, per-record)You want orchestration codified as a re-runnable script plus a shared brief, not improvised turn by turnQuality matters more than token economy - independent attempts cross-checked and refuted before you trust the answerCodebase-wide sweeps, 100+ file migrations, multi-round refactor campaigns, multi-angle research

SKILL.md 正文

来源 NousResearch/hermes-agent@0b89435 · 许可 MIT · 内容未修改

Dynamic Workflow Skill

Runs large fan-out work as a workflow: the plan, the loop and every intermediate

result live in a script and on disk, so the parent's context holds only verified

results. Covers one-shot fan-outs, adversarial convergence (attempts + refuters),

and multi-wave campaigns that integrate dozens of worker branches. It does not

make delegate_task durable across restarts; that is the kanban swarm's job.

When to Use

Reach for it when the unit of work is clear (a file, an endpoint, a record) and

there are more units than one context can hold. Skip it for under ~10 units or

for serial chains. For a refactor or fix campaign on hermes-agent itself, load

hermes-agent (the dev workflow) alongside; this skill owns the fan-out shape.

Prerequisites

  • delegate_task available and delegation.max_concurrent_children sized for

the wave (default 10; the runtime rejects a tasks=[] larger than that with a

clear error rather than queueing). delegation.max_spawn_depth >= 2 only if

children must fan out themselves.

<!-- no-tmp: ok — explains why a literal /tmp is wrong -->

  • A writable run directory resolved from the terminal environment's temp dir ($TMPDIR, else the platform temp dir). Never a literal /tmp:

Termux has no such directory and native Windows breaks on it. Use <tmp>/wf_<name>_<uuid>/, unique per

run, so an interrupted earlier run cannot leave stale outputs to be misread.

  • execute_code for the deterministic layer (only web_search, web_extract,

read_file, write_file, search_files, terminal, patch exist inside it).

How to Run

Two layers, split by a real capability boundary:

Layer A - execute_code scriptLayer B - delegate_task batch
Use forDETERMINISTIC work: fetch N URLs, parse N files, run N commands, template N outputs, build manifests, merge outputsLLM-JUDGMENT work: classify, review, decide, write, refute, refactor one unit
Holdsloop, branching, intermediate variablesnothing; one call with tasks=[...], each task its own isolated agent
Toolsthe sandbox set above; it can NOT call delegate_taskthe parent's toolsets, inherited unchanged (no per-task narrowing); children lose delegate_task, clarify, memory, send_message, cronjob_manage
Concurrencyyours (ThreadPoolExecutor, batches)bounded by delegation.max_concurrent_children
Costtool calls onlyone full agent tree per task; multiplies linearly

Do the deterministic part in Layer A first, fan out only the irreducibly-LLM

step in Layer B, synthesize on the parent.

Background-first: results re-enter as messages

A top-level delegate_task returns immediately with one handle per task; each

child's result re-enters the conversation as a new message when it finishes. You

cannot read out_*.csv on the line after the call. Finish whatever does not

depend on the children, give a one-line status, and END YOUR TURN; act on each

result message as it lands. An ordinary follow-up user message does not cancel

children; /stop, /new and process exit do. Only a delegation issued by an

orchestrator subagent (depth > 0) is synchronous.

Quick Reference

  • Unit must be answerable without sibling output, else it is serial.
  • Manifest: one unit per line in <run>/manifest.jsonl; print count + run dir.
  • Per child: ~8-12 mechanical edits, or ~2-3k lines of reading, or ~50-70 KB of

corpus; size by the LARGEST unit. Structured output goes to files, never the

summary field (it truncates under load); delimiter-separated lines over JSON.

  • Parent verifies file count and per-run freshness before merging.
  • A "stalled" child usually completed its write; check the filesystem first.
  • Scoped slice first (one directory, 20 records), report token cost, then scale.

Procedure

One-shot fan-out

  1. Decompose into independent units.
  2. Layer A pre-pass writes the manifest.
  3. Size chunks against the limits above; for more tasks than

max_concurrent_children, issue bounded waves yourself.

  1. Layer B: one delegate_task(tasks=[...]); each task reads its slice, writes

<run>/out_<i>.csv, prints a status word, stops.

  1. End the turn. As result messages arrive, read the files, verify, merge; the

cross-cutting synthesis stays on the parent.

Adversarial convergence (finding-quality work)

  1. Independent attempts: the SAME question to N children (2-4) with DIFFERENT

framings in each context, each writing one claim per line to

<run>/attempt_<i>.md. Located, individually falsifiable claims only

("POST /api/users/:id/role in src/routes/users.ts:142 has no role check");

a refuter cannot break "the auth layer has problems".

  1. Merge and dedupe on the parent; note the agreement count per claim.
  2. Refuters: a second batch told to BREAK each claim with counter-evidence,

emitting claim_idx|survives|counter_evidence. Give them the sources, not the

attempts' reasoning.

  1. Surface only survivors; drop refuted claims with a one-line reason.
  2. Feed new claims from round 2 through one more refutation; stop when a round

adds no survivors, cap at 3 rounds.

The same mechanic protects the parent from its own wrong premises: when you

hand children a heuristic ("every patch target on a facade is a dead seam"),

tell them to refute it with evidence before acting on it. Four squads doing so

turned a 647-site blanket rewrite into 59 real fixes and saved 130+ green tests.

Campaign shape (dozens of workers, several waves, hours)

The one-shot recipe does not scale to a whole-codebase pass. What did:

  1. Measure first (LOC, hotspots, dead symbols, oracle corpora) and write ONE

shared BRIEF.md plus a per-cluster task_<cluster>.md. Every child reads

both. When the fleet drifts (children shaving docstrings instead of cutting

code), patch the brief once and steer; re-dispatched children inherit the fix.

  1. Exclusive ownership: one cluster of files per worker, edits outside it are

discarded at integration. Sub-fan-outs inside one file own line RANGES and

define helpers inside their range so diffs merge cleanly.

  1. Commit per verified step, locally, no push, no PR, no rebase from children.

Committed state is the only handoff; every worker that died mid-campaign lost

exactly its uncommitted tail. A worker sharing a worktree index commits with

git commit -- <paths> only; a bare commit swept a sibling's staged hunks.

  1. Fleet size 12-16 concurrent. Above ~40 processes on one OAuth grant the

hourly token refresh stampedes into 401s and kills the wave. Queue the rest.

  1. Parent liveness: a child reporting completed with a few dozen log lines, or

with 0 commits on its branch, has not finished; look for its sub-branches or

re-dispatch it with the predecessor's worktree and diff.

  1. Integration per round: freeze a base SHA, rebase clean branches mechanically,

give each conflicting branch its own rebase worker ("main's behaviour wins,

re-applied inside the new structure"), merge onto one integration branch,

run the FULL suite on the combined tree. Collisions that every branch passed

alone appear only here. The next round branches from the integrated commit

so its workers cannot conflict with each other.

  1. Before declaring a round integrated: git rev-list --count <integration>..<branch>

is 0 for EVERY branch. Workers keep committing after you merge their tip;

168 commits across six slices were once left behind that way.

  1. Test runs: exactly one runner on the box, behind a lock file, at high -j.

Many parallel low--j runners were slower AND killed each other's process

groups. Red files are re-run on a bare origin/main worktree in the same

venv; identical per-file failure sets are pre-existing, not yours.

  1. Forward-port at the end, not per round: freeze main's SHA, fan out the

conflicted files by directory to workers editing ONE merge worktree with

no commits, then the parent commits the merge once. CI never runs on a

conflicted PR, so re-merge main before every push.

  1. Live QA is its own wave: one squad per surface, isolated HERMES_HOME,

expectation written before the check, evidence on disk, report only, and a

PR-vs-main difference is the only thing that counts as a regression. Green

unit tests missed the one P0 (a logged-in code path no test exercised).

  1. Reviewer claims get the same treatment as child claims: A/B against the

base before "restoring" anything. Several confidently stated review deltas

already behaved that way on base.

  1. A parent restart needs a HANDOFF.md: why it died, which handles are dead,

per-branch scorecard (LOC delta, import smoke, targeted tests), and the exact

re-dispatch text. Snapshot every dirty worktree into a wip: commit first.

Pitfalls

  • Calling delegate_task inside an execute_code script: not in the sandbox.
  • Synthesizing on the same turn as the fan-out call: the files do not exist yet.
  • Promising background-durable-for-days from delegate_task: it is turn-scoped

and dies with the process. Durable graph = kanban swarm; one-off = cronjob.

  • Trusting summary for content, or status=completed for completion.
  • Same framing in every "independent" attempt: they collapse to one answer.
  • git stash anywhere in a worktree campaign: refs/stash is shared across

worktrees and another worker will pop your edits. Compare via a temp worktree.

  • Reporting a hit target when the honest number is lower. Say "16% so far, here

is the path to 30%" and run the next round.

Verification

  • Manifest line count matches the expected unit count.
  • Every out_*.csv exists and was written this run.
  • Every dropped claim has recorded counter-evidence; every surfaced claim went

through refutation.

  • Campaign: every branch at 0 unmerged commits, full suite on the integrated

tree with reds triaged against bare main, live QA report per surface, token

cost reported on the scoped slice before the full run.

质量与来源

所属仓库
NousResearch/hermes-agent
仓库星标
25 万
最近更新
今天
采集时间
今天
commit
0b89435e7e4f
内容指纹
sha256:a030cce5a966e68
文件路径
optional-skills/autonomous-ai-agents/dynamic-workflow/SKILL.md

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