dynamic-workflow 精选
Plan-in-code fan-outs, adversarial verification, waves.
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/
https://raw.githubusercontent.com/NousResearch/hermes-agent/0b89435e7e4f7fab88a34eb69f13bf339eb2fd00/optional-skills/autonomous-ai-agents/dynamic-workflow/SKILL.md下载后另存为 ~/.claude/skills/dynamic-workflow/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
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:
gitmake - 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。
SKILL.md 正文
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_taskavailable anddelegation.max_concurrent_childrensized 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_codefor the deterministic layer (onlyweb_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 script | Layer B - delegate_task batch | |
|---|---|---|
| Use for | DETERMINISTIC work: fetch N URLs, parse N files, run N commands, template N outputs, build manifests, merge outputs | LLM-JUDGMENT work: classify, review, decide, write, refute, refactor one unit |
| Holds | loop, branching, intermediate variables | nothing; one call with tasks=[...], each task its own isolated agent |
| Tools | the sandbox set above; it can NOT call delegate_task | the parent's toolsets, inherited unchanged (no per-task narrowing); children lose delegate_task, clarify, memory, send_message, cronjob_manage |
| Concurrency | yours (ThreadPoolExecutor, batches) | bounded by delegation.max_concurrent_children |
| Cost | tool calls only | one 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
- Decompose into independent units.
- Layer A pre-pass writes the manifest.
- Size chunks against the limits above; for more tasks than
max_concurrent_children, issue bounded waves yourself.
- Layer B: one
delegate_task(tasks=[...]); each task reads its slice, writes
<run>/out_<i>.csv, prints a status word, stops.
- 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)
- 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".
- Merge and dedupe on the parent; note the agreement count per claim.
- 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.
- Surface only survivors; drop refuted claims with a one-line reason.
- 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:
- 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.
- 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.
- 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.
- 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.
- Parent liveness: a child reporting
completedwith 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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_taskinside anexecute_codescript: 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
summaryfor content, orstatus=completedfor completion. - Same framing in every "independent" attempt: they collapse to one answer.
git stashanywhere in a worktree campaign:refs/stashis 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_*.csvexists 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