Agent skill

Deerflow Maintainer Orchestrator

by bytedance in bytedance/deer-flow

A skill your agent uses when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review…

MITAuto-check passedDevelopment

Install Deerflow Maintainer Orchestrator

skills CLI
$ npx skills add bytedance/deer-flow --skill deerflow-maintainer-orchestrator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install bytedance/deer-flow deerflow-maintainer-orchestrator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agent/skills/deerflow-maintainer-orchestrator .claude/skills/deerflow-maintainer-orchestrator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deerflow-maintainer-orchestrator
GitHub stars
84k
Token cost
~5.4k tokens
SKILL.md length
2,846 words
Files
1
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review…

  • Works in 12 steps: Default repository is… → For URLs, route /issues/ to Issue Flow… → For typed numbers, use the typed command → …
  • A DeerFlow maintainer needs comment-only GitHub issue
  • SKILL.md covers Core Rule, Artifact Resolution, Existing Coverage and Re-Runs and Issue Flow, plus 7 more sections
  • Calls gh, git and make; needs BETTER_AUTH_SECRET

What it does

Deerflow Maintainer Orchestrator is an agent skill from bytedance/deer-flow. Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.

Its SKILL.md is about 5.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Pull requests and Legal risk assessment. It works with GitHub. The repository describes itself as: An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles… The licence is MIT.

When your agent uses it

  • A DeerFlow maintainer needs comment-only GitHub issue
  • PR handling: resolve issue/PR scopes with gh
  • Draft issue comments
  • Perform PR review comments

Example prompts

  • “/deerflow-maintainer-orchestrator”

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. Default repository is bytedance/deer-flow unless a URL or explicit repo says otherwise.
  2. For URLs, route /issues/ to Issue Flow and /pull/ to PR Review Flow.
  3. For typed numbers, use the typed command
  4. Normalize multiple explicit references such as #123, # 123, and bare 123 into a number list, preserving order and de-duplicating exact…
  5. For untyped numbers, try gh pr view --repo --json number,url first. If it fails, use gh issue view --repo --json number,url. Do not ask…
  6. For issue batches, use gh issue list, not the mixed GitHub issues endpoint. For PR batches, use gh pr list.
  7. Respect maintainer-provided count or time window. There is no hard five-item cap. If the scope is broad and underspecified, choose a…
  8. For "recent/latest" wording without a count, use a small default recent slice. For "recent hours" wording without a number, use six hours…
  9. Use gh api when gh issue/pr view/list lacks required fields such as timeline events, review threads, or precise search filters.
  10. Use GitHub search only as a fallback for natural-language filters that cannot be represented by view/list/API calls. Do not use web search…
  11. When an issue has more than one candidate resolving PR, gather them all before reviewing: the issue's linked/Development PRs, closing…
  12. If no artifact type, number, URL, count, time window, or searchable GitHub scope can be resolved, stop with a compact "scope unresolved"…

What it can do on your machine

Read from SKILL.md and the folder at commit ab9920f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh
    • git
    • make
    • pnpm
    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh, git, pnpm and uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • BETTER_AUTH_SECRET

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deerflow Maintainer Orchestrator loads about 5.4k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 2,846 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~110
When it runs · the whole SKILL.md, loaded when a task matches
~5.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from bytedance/deer-flow at commit ab9920f, republished under its MIT licence (© bytedance). 2,846 words, ~5,354 tokens.

Download SKILL.mdSave it as .claude/skills/deerflow-maintainer-orchestrator/SKILL.md (or your agent's skills folder).
name
deerflow-maintainer-orchestrator
description
Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.

DeerFlow Maintainer Orchestrator

Core Rule

This is a comment-plane skill: resolve GitHub scope, inspect evidence, and prepare or post DeerFlow issue comments and PR review comments. Keep the work comment-scoped; do not turn it into coding, branch management, release work, artifact closure, or other maintainer operations.

When the maintainer asks to process, handle, comment on, or review a bounded set of issues or PRs, proceed without asking follow-up questions. Treat that request as authorization for one public issue comment per selected non-skipped issue and one PR review comment per selected PR with high-confidence findings. If a PR has no high-confidence findings, do not post a public comment; report that result to the maintainer only. If the maintainer explicitly asks for analysis only, return comment-ready drafts without posting.

The maintainer's normal interaction should be: provide scope; receive posted comment URLs, PR review URLs, clean results, skipped items, failures, or drafts. Do not offload technical analysis to the maintainer. Make the best evidence-backed recommendation in the comment itself: describe the risk, impact, likely fix, and validation path. Ask the reporter or PR author for missing evidence only when the artifact lacks enough data to diagnose.

Output only the maintainer run result or comment draft. Do not announce the skill name, mode, or that no code was edited unless the user asks for process details.

Match the dominant language of the issue or PR unless the maintainer asks for another language. Chinese issue or PR text gets Chinese output; English issue or PR text gets English output. For mixed artifacts, use the body language, not logs or code.

Artifact Resolution

Use GitHub tooling to resolve artifact type and scope. Do not ask the maintainer to clarify when gh or GitHub API can determine the answer.

  1. Default repository is bytedance/deer-flow unless a URL or explicit repo says otherwise.
  2. For URLs, route /issues/<number> to Issue Flow and /pull/<number> to PR Review Flow.
  3. For typed numbers, use the typed command:
    • Issue: gh issue view <number> --repo <repo> --json number,title,url,state,body,labels,author,comments
    • PR: gh pr view <number> --repo <repo> --json number,title,url,state,body,author,files,comments,reviews,statusCheckRollup,baseRefName,headRefName
  4. Normalize multiple explicit references such as #123, # 123, and bare 123 into a number list, preserving order and de-duplicating exact repeats.
  5. For untyped numbers, try gh pr view <number> --repo <repo> --json number,url first. If it fails, use gh issue view <number> --repo <repo> --json number,url. Do not ask which type it is.
  6. For issue batches, use gh issue list, not the mixed GitHub issues endpoint. For PR batches, use gh pr list.
  7. Respect maintainer-provided count or time window. There is no hard five-item cap. If the scope is broad and underspecified, choose a practical recent slice, state the slice used, prioritize newest and highest-risk items, and report any unprocessed remainder.
  8. For "recent/latest" wording without a count, use a small default recent slice. For "recent hours" wording without a number, use six hours. Do not ask.
  9. Use gh api when gh issue/pr view/list lacks required fields such as timeline events, review threads, or precise search filters.
  10. Use GitHub search only as a fallback for natural-language filters that cannot be represented by view/list/API calls. Do not use web search for artifact routing unless GitHub tooling is unavailable.
  11. When an issue has more than one candidate resolving PR, gather them all before reviewing: the issue's linked/Development PRs, closing keywords (Closes/Fixes #<issue>) found via gh api timeline cross-reference events, and PRs that mention the issue. Route them into Competing PR Comparison.
  12. If no artifact type, number, URL, count, time window, or searchable GitHub scope can be resolved, stop with a compact "scope unresolved" report. Do not ask a follow-up question.

Use concise repo-local references such as #123 and PR #123 in maintainer reports and comments. Include full GitHub URLs only for posted comment/review links returned by GitHub or when the maintainer supplied an explicit URL.

Existing Coverage and Re-Runs

Existing comments suppress duplicate posting, not analysis. Always analyze the artifact in full, then post only the net-new delta over what is already covered.

  1. Read existing maintainer/trusted-agent comments and reviews as prior coverage.
  2. Analyze the artifact fully regardless of what already exists. A prior comment may be partial — catching A while missing B.
  3. Keep only net-new, high-confidence items not already materially covered.
  4. Non-empty delta: post one comment that explicitly builds on the prior coverage (for example Adding to @reviewer's review:) and states only the new items. Do not restate covered points.
  5. Empty delta: post nothing public; report Already covered to the maintainer with the existing comment/review URL.
  6. Idempotency: treat your own earlier skill-authored comments as already-covered. On a re-run, never stack a second comment that repeats an earlier one — post only genuinely new delta, or nothing.

RFC issues are the one hard skip: no analysis and no post unless the maintainer overrides.

Issue Flow

Use Issue Flow for GitHub issues, bug reports, feature requests, support questions, and issue batches.

Start every issue with a cheap precheck:

  1. Fetch issue metadata, labels, author, body, and existing comments.
  2. If labels, title, or body mark the issue as RFC (rfc, [RFC], RFC:, or Request for Comments), classify it as rfc-no-comment, skip deep analysis, and do not post anything public unless the maintainer explicitly overrides the RFC skip for that item.
  3. Existing maintainer or trusted-agent comments are prior coverage, not an automatic skip. Analyze fully and post only the net-new delta (see Existing Coverage and Re-Runs).
  4. Treat ordinary reporter replies, thanks, unrelated discussion, or incomplete guesses as non-blocking.
  5. Report already-covered or skipped issues to the maintainer only as compact identifiers plus the reason or existing comment URL when available.

For non-skipped issues:

  1. Read enough context to avoid guessing: issue body, comments, screenshots, logs, reproduction details, linked artifacts, and relevant DeerFlow code/docs.
  2. Classify the surface:
    • Frontend UI
    • Backend API
    • Agents / LangGraph
    • Sandbox
    • Skills
    • MCP
    • Dependencies
    • Default behavior
    • Docs / tests / CI only
  3. Classify actionability:
    • ready-to-fix: bounded, evidence sufficient, validation path clear.
    • needs-more-evidence: repro, logs, environment, screenshots, exact expected behavior, or failing case missing.
    • defer-or-close: duplicate, stale, unsupported, unactionable, or out of scope.
    • rfc-no-comment: RFC issue; skip public comments by default.
  4. Produce a public-safe comment from the analysis, not the analysis labels:
    • Start with one natural opener that connects to the issue context. Prefer Thanks @author. for reporter-authored issues when it reads naturally; omit the mention for bots, maintainer-authored tracking issues, or cases where it would add noise.
    • The opener must say something specific about the next step or boundary, not a generic assessment. Do not use generic phrases such as "This is actionable", "I would treat this as", "ready to fix", or surface/actionability/risk labels.
    • Use the smallest stable template that fits:
text
Thanks @author. <one specific sentence that frames the fix, investigation, or missing evidence.>

Recommended solution:
- ...

Validation:
- ...
  • Add Evidence: only when citing concrete code, logs, reproduction details, or other proof helps the author act.
  • Add Risk: only when architecture, security, public API, default behavior, or compatibility impact must be called out explicitly; make the risk specific.
  • Add Missing info: only when the issue cannot be diagnosed without more evidence; ask for the smallest useful data.
  • Put relevant files/components inside Evidence: or Recommended solution: bullets instead of separate metadata fields.
  • Every posted issue comment should contain concrete modification guidance and validation guidance unless the only useful response is Missing info:.
  1. Immediately before posting, refresh comments; fold any equivalent comment that appeared during analysis into prior coverage and post only the remaining delta.
  2. Post one issue comment when posting is authorized; otherwise return the same text as Reply draft.

Do not expose private reasoning, credentials, internal-only context, or unsupported promises. Do not say a fix was made unless a separate coding workflow actually changed code.

PR Review Flow

Use PR Review Flow for GitHub pull requests and PR batches.

Start every PR with a cheap precheck:

  1. Fetch PR metadata, changed file list, checks summary, existing PR reviews, existing PR comments, and review threads when available.
  2. Existing maintainer or trusted-agent reviews are prior coverage, not an automatic skip. Review fully and post only the net-new delta (see Existing Coverage and Re-Runs).
  3. Read statusCheckRollup as signal, not verdict. Failing required checks are themselves a reportable finding (build failure = P0; failing tests or lint = P1/P2 by impact). Green checks lower risk but never excuse reading the actual changed code path — confirm suspect logic by reading the source, not by trusting green CI. Tests passing does not prove the changed branch is exercised.
  4. Treat author replies, thanks, unrelated discussion, or incomplete guesses as non-blocking.
  5. Report already-covered or clean PRs to the maintainer only, with the existing review/comment URL when available.
Show full SKILL.md (1,413 more words)Show less
Diff Base Rule

Before reviewing a local PR branch or local diff, fetch the base repository's target branch and compare against that fresh remote-tracking ref, not a possibly stale local main.

  • For fork checkouts, prefer upstream/<base-branch> when upstream points to the base repository.
  • For direct upstream checkouts, use the base remote's fetched branch, usually origin/<base-branch>.
  • Prefer GitHub PR base metadata for the target branch. For non-PR local diffs, use the base repository default branch. If metadata is unavailable, default to main only after fetching the base remote.
  • Refresh the comparison ref explicitly, for example git fetch <base-remote> +refs/heads/<base-branch>:refs/remotes/<base-remote>/<base-branch>, then inspect BASE=$(git merge-base HEAD <base-remote>/<base-branch>) and git diff "$BASE"...HEAD.
  • If using FETCH_HEAD from a single-branch fetch instead, diff against that verified FETCH_HEAD immediately and do not later substitute a possibly stale remote-tracking ref.
  • Resolve the PR head explicitly. For fork PRs whose head branch is not on the base repo, fetch the PR ref: git fetch <base-remote> pull/<n>/head:pr-<n>. The fork's own branch ref and gh api .../contents?ref=<fork-branch> will 404 against the base repo. Record the head SHA you reviewed.
  • Re-check the head SHA immediately before posting. If the PR head moved during analysis, re-review the new diff or abort — never post a review against a diff the PR no longer has.
  • For uncommitted local changes, review committed branch changes against the fresh base first, then include working-tree changes separately.
  • If the base remote or base branch cannot be established, use the GitHub PR files/diff as the source of truth. If neither local nor GitHub diff can be read, return a compact failure report and do not post a review.

Before posting a PR review comment:

  1. Review only the current diff against the fresh base and changed files. Do not comment on unrelated pre-existing code unless the diff makes it newly risky.
  2. Do not report low-confidence guesses. If evidence is insufficient, omit the finding.
  3. Prioritize correctness, safety, maintainability, production risk, compatibility, and missing critical tests over style.
  4. Report concrete architecture, security, public API, default-behavior, and compatibility problems as findings when the diff causes or exposes them.
  5. Check changed behavior, edge cases, error paths, state mutation, transactions, locks, cache invalidation, cleanup, security boundaries, missing tests, performance/reliability, and API compatibility.
  6. Immediately before posting, refresh reviews/comments and fold any equivalent review that appeared during analysis into prior coverage; post only the remaining delta.
  7. Apply the Posting Gate. If the gate yields public findings, post one PR review comment in the PR language. Otherwise post nothing public and report the result (No high-confidence review findings. or Already covered) plus any sub-threshold items as Maintainer notes.

For public PR reviews with findings, start with one short opener that fits the review context and matches the finding count. Use singular wording only for exactly one finding, for example Thanks @author. I found one issue that should be addressed before this is ready. Use plural wording for multiple findings, for example Thanks @author. I found a few issues that should be addressed before this is ready. Omit the mention for bots or when it adds noise.

For each finding, use:

text
[P0/P1/P2] Title

- Location: file and line/range
- Problem: what can go wrong
- Evidence: why the diff causes it
- Suggested fix: concrete minimal fix
- Test: what test should cover it

Severity guide:

  • P0: causes outage, data loss, security breach, or build failure.
  • P1: likely production bug, serious regression, broken compatibility, or high-risk security/architecture issue.
  • P2: correctness, maintainability, or test concern with lower risk.
Posting Gate

Posting depends on BOTH confidence (is the problem real?) and severity (how bad if real). They are independent axes — "no high-confidence findings" means none across P0/P1/P2, not merely "no P0".

  • Post publicly only items that are high-confidence AND at least P2.
  • For a public P2, additionally require that the diff itself introduces or worsens the issue. Do not raise a public P2 for pre-existing behavior the diff only touches, or for a change that is a net improvement over the prior state.
  • A high-confidence P0/P1 is always worth posting. A low-confidence P1 is not — omit it, or route it to Maintainer notes framed as a hypothesis to verify.
  • Sub-threshold but real observations (net-improvement nits, bounded or low-risk concerns, pre-existing issues, low-confidence hypotheses) go to the Maintainer notes channel in the run result, never to a public comment.

Do not produce compliments, summaries, or general advice. For sensitive security issues, describe impact and remediation without exploit instructions.

Batch Handling

When the scope has multiple artifacts, cluster before reviewing and synthesize after.

Cluster by relatedness, not by type. Group artifacts that share files, interfaces, or the same issue/feature into one cluster; same-type artifacts that touch disjoint files are independent.

  • Related cluster: review in ONE shared context so cross-artifact reasoning is possible — parallel agents cannot see each other's findings. If it cannot fit one context, fan out per sub-group and reconcile in the synthesis pass; never split it blind, without that re-aggregation.
  • Independent clusters: may run in parallel. Offloading a large or independent batch to one subagent per cluster keeps the main context clean — consider it for big batches, prefer offering it to the maintainer over silently spawning, and do not spawn for two or three related items or when the cold-start cost is not earned.

After per-artifact review, run one synthesis pass over the whole batch and report it to the maintainer (decision-support, not a public comment):

  • Overlapping files and merge-order/conflict surface — which PRs touch the same files and will conflict pairwise.
  • Duplicate or competing solutions to the same problem.
  • Composition risk — changes each safe alone but interacting (for example, two PRs editing the same module or table).

Competing PR Comparison

When several PRs target the same issue, compare them instead of reviewing each in isolation.

  1. Pull the issue's acceptance criteria (reported problem and expected behavior); that is the rubric anchor.
  2. Score each PR on: does it actually resolve the issue's ask; correctness and edge/error-path coverage; test quality; blast radius and compatibility; maintainability. Use the same DeerFlow Review Heuristics and Posting Gate as a single review.
  3. Report a maintainer-facing comparison — strongest PR and why, what each is missing — in the run result.
  4. Keep the public surface constructive and per-PR: post each PR's own gate-passing findings normally. Do not publicly rank PRs against each other or tell an author their PR is worse than a competitor's; winner selection stays in the maintainer report.

No-Question Policy

Do not ask the maintainer routine clarification questions. The skill should save maintainer time by turning scope into comments through a fixed workflow.

Stop without asking only when:

  • no issue/PR scope can be resolved through URLs, numbers, gh view/list, gh api, or GitHub search fallback;
  • GitHub authentication, repository access, or comment posting fails;
  • the requested action is outside comment-only scope;
  • posting would require private credentials, private security details, or non-public context.

In these cases, return a compact failure report with the attempted command path and the smallest next action. Do not phrase it as a question unless the maintainer explicitly asked to be prompted.

DeerFlow Review Heuristics

Treat these as high-signal areas for issue comments and PR findings:

  • backend/packages/harness/deerflow/ must not import app.*.
  • App may depend on harness; harness must stay publishable and app-agnostic.
  • Frontend thread/message behavior and Gateway/LangGraph-compatible SSE are contract surfaces.
  • Sandbox permissions, bash/file-write tools, skill installation, and remote execution are security-sensitive.
  • Default model/provider behavior, config migration, persistence schema, public API/SSE, and LangGraph thread/run lifecycle are compatibility-sensitive.
  • Runtime docs should track user-facing or developer-facing behavior changes.
  • Security-sensitive comments should provide proof and remediation, not vague assertions.

Validation Guidance

Recommend the checks matching the touched surface:

SurfaceSuggested validation
Backend API / harness / agents / MCP / skills runtimecd backend && make lint && make test
Blocking IO or async file/network workcd backend && make test-blocking-io or a focused blocking-IO regression
Harness/app boundarycd backend && uv run pytest tests/test_harness_boundary.py
Frontend UI/corecd frontend && pnpm format && pnpm lint && pnpm typecheck && BETTER_AUTH_SECRET=local-dev-secret pnpm build && make test
Front/back thread or SSE contractbackend replay golden and full-stack replay render where feasible
Frontend user workflowPlaywright E2E or browser proof with screenshot/DOM assertion
Docker/sandbox/provisionerfocused backend tests plus Docker/provisioner smoke when feasible
Docs-onlytargeted markdown review

Output

For Issue Flow:

text
Run result:
Posted:
Skipped:
Already covered:
Failed:
Maintainer notes:
Per issue:
  Issue:
  Surface:
  Actionability:
  Risk:
  Comment:
  Validation:
  Comment status:

For PR Review Flow:

text
Run result:
Reviewed:
Skipped:
Clean:
Already covered:
Failed:
Maintainer notes:
Per PR:
  PR:
  Public review:
  Findings:
  Review status:

For analysis-only requests, replace Posted/Reviewed with Drafted and include the comment/review text without posting.

For batches, prefer a compact maintainer-facing table after the headline counts:

text
| Artifact | Status | Public action | Notes |
| --- | --- | --- | --- |
| #123 | posted | comment URL | short reason |
| PR #456 | reviewed | review URL | P1: finding title |
| PR #789 | clean | none | No high-confidence review findings. |
| #321 | already covered | none | existing maintainer comment |

For multi-artifact batches, follow the table with a Batch synthesis block (overlapping files, merge-order/conflict surface, duplicate or competing solutions, composition risk) and, when issues had competing PRs, a Competing PR comparison block. Both are maintainer-only.

Omit empty categories, no-op fields, routine command output, and raw logs. Report meaningful changes, evidence, and options.

© bytedance, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agent/skills/deerflow-maintainer-orchestrator of bytedance/deer-flow.

Open the folder on GitHubat commit ab9920f

Compare with similar skills

Deerflow Maintainer Orchestrator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deerflow Maintainer Orchestrator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deerflow Maintainer Orchestrator this skillbytedance/deer-flow84k—~5.4kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
Contributor-First PR MergeHKUDS/OpenHarness16k1 repos~847Automated safety check: PassMIT
Create Pull Requestcline/cline70k1 repos~1.6kAutomated safety check: PassApache-2.0
Pull Request Title and Body Writeropeninterpreter/openinterpreter69k2 repos~1.1kAutomated safety check: PassApache-2.0

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    84k GitHub starsUsed in 4 repos~2.2k tokens
    Auto-check passed
  • Structured Image Generation

    bytedance/deer-flow

    Turns an image request into a structured JSON prompt and runs a bundled Python script to generate the picture, optionally guided by reference images.

    84k GitHub starsUsed in 4 repos~2.9k tokens
    Auto-check passed
  • DeerFlow Smoke Test

    bytedance/deer-flow

    Walks through an end-to-end smoke test of a DeerFlow deployment: pull the latest code, deploy with Docker or locally, verify services, run health checks and write a report.

    84k GitHub stars~2.5k tokensUpdated today
    Auto-check: notes

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Questions about Deerflow Maintainer Orchestrator

What does Deerflow Maintainer Orchestrator do?

A skill your agent uses when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review…. Deerflow Maintainer Orchestrator is an agent skill from bytedance/deer-flow. Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance.

When should I use Deerflow Maintainer Orchestrator?

Deerflow Maintainer Orchestrator fits situations like: A DeerFlow maintainer needs comment-only GitHub issue; PR handling: resolve issue/PR scopes with gh; draft issue comments; perform PR review comments.

How do I install Deerflow Maintainer Orchestrator in Claude Code?

Run `npx skills add bytedance/deer-flow --skill deerflow-maintainer-orchestrator -a claude-code`. Or copy the skill folder (.agent/skills/deerflow-maintainer-orchestrator in bytedance/deer-flow) into .claude/skills/deerflow-maintainer-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Deerflow Maintainer Orchestrator in Codex?

Run `npx skills add bytedance/deer-flow --skill deerflow-maintainer-orchestrator -a codex`. Or copy the skill folder (.agent/skills/deerflow-maintainer-orchestrator in bytedance/deer-flow) into .agents/skills/deerflow-maintainer-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Deerflow Maintainer Orchestrator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bytedance/deer-flow --skill deerflow-maintainer-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deerflow-maintainer-orchestrator, .gemini/skills/deerflow-maintainer-orchestrator, .github/skills/deerflow-maintainer-orchestrator and .opencode/skills/deerflow-maintainer-orchestrator in your project.

What does Deerflow Maintainer Orchestrator need to run?

Going by SKILL.md and its folder, Deerflow Maintainer Orchestrator needs the command-line tools its instructions call (gh, git, make, pnpm and uv) and credentials named BETTER_AUTH_SECRET.

Does Deerflow Maintainer Orchestrator access the network?

SKILL.md contains no URLs. Its commands use gh, git and uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Deerflow Maintainer Orchestrator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deerflow Maintainer Orchestrator use?

Deerflow Maintainer Orchestrator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deerflow Maintainer Orchestrator use?

About 5.4k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deerflow Maintainer Orchestrator?

Skills that share tags, products or a category with Deerflow Maintainer Orchestrator: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars), Contributor-First PR Merge (HKUDS/OpenHarness, 16k stars) and Create Pull Request (cline/cline, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deerflow Maintainer Orchestrator?

bytedance (a GitHub organization) maintains it in bytedance/deer-flow, which has 83,611 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 10, 2026.

Source: bytedance/deer-flow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.