Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .claude/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .agents/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .cursor/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .gemini/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .github/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "dify-docs-feature-research" agent skill from https://github.com/langgenius/dify-docs/tree/main/.claude/skills/dify-docs-feature-research into .opencode/skills/dify-docs-feature-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dify-docs-feature-research", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
dify-docs-feature-research
GitHub stars
178
Token cost
~2.6k tokens
SKILL.md length
1,129 words
Files
2 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
CC-BY-4.0
At a glance
Research a Dify feature before writing or optimizing documentation.
Works in 3 steps: Codebase Investigation → Community Feedback → Synthesize
Starting any doc task that requires understanding a features implementation
SKILL.md covers Depths, Before Starting, Research Process and Important
Calls gh
What it does
Dify Docs Feature Research is an agent skill from langgenius/dify-docs. Research a Dify feature before writing or optimizing documentation. Use when starting any doc task that requires understanding a feature's implementation, user pain points, or community feedback. Triggers: 'research this feature', 'investigate the code for', 'what do users say about', 'let's understand how X works before writing', or any documentation task where the current docs are being rewritten or significantly expanded.
Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/detection-tables.md`).
It works with Dify. The licence is CC-BY-4.0.
When your agent uses it
Starting any doc task that requires understanding a features implementation
User pain points
Community feedback
Example prompts
“s implementation, user pain points, or community feedback. Triggers:”
“investigate the code for”
“what do users say about”
“/dify-docs-feature-research”
Requirements
Docker
Workflow steps
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 45d4e56. 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
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use gh, 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 no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Dify Docs Feature Research loads about 2.6k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 114 tokens; SKILL.md has 1,129 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~114
When it runs· the whole SKILL.md, loaded when a task matches
~2.6k
With references· SKILL.md plus every file in references/, read only if the agent opens them
~4.2k
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.
Download SKILL.mdSave it as .claude/skills/dify-docs-feature-research/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
dify-docs-feature-research
description
Research a Dify feature before writing or optimizing documentation. Use when starting any doc task that requires understanding a feature's implementation, user pain points, or community feedback. Triggers: 'research this feature', 'investigate the code for', 'what do users say about', 'let's understand how X works before writing', or any documentation task where the current docs are being rewritten or significantly expanded.
Dify Feature Research
Pre-writing research that combines codebase analysis with community feedback to ensure documentation is grounded in both technical reality and actual user needs.
Depths
When invoked from the dify-docs-write pipeline, its S1 supplies the feature, ref, and target pages — consume them instead of re-asking (Before Starting 1–3), and run at the depth the caller sets:
full: everything below.
targeted: Phase 1 scoped to the surfaces the caller names — the coverage gate still applies, with out-of-scope surfaces recorded as N/A plus why; Phase 2 runs when the caller requires it; otherwise skip it and say so in the summary.
Standalone use (no caller): run Before Starting 1–3 and full depth.
Before Starting
Ask the user which feature, node, or area to research.
Confirm which dify ref to investigate (default: main). For graphon, the default is the version dify pins (step 6), never graphon main.
Check if the user has a specific doc page in mind for the rewrite.
Locate the repos: use the dify and graphon working directories configured for this session (langgenius/dify and langgenius/graphon on GitHub). If either is absent, ask the user for its path.
Sync and read code at the target ref by following "Syncing the Dify codebase safely" in writing-guides/index.md.
Resolve the graphon pin. dify pins graphon to an exact version; verify graphon behavior at that tag. From the dify repo root:bash
grep '"graphon' api/pyproject.toml
# e.g. "graphon==0.6.0" → read graphon at tag v0.6.0, not main
Behavior read from graphon main may not exist in the version users run. Ask the user before researching graphon main (appropriate only when documenting something they know is about to ship).
Research Process
Run Phase 1 and Phase 2 in parallel: dispatch one subagent per phase. If subagents are unavailable, run Phase 1 first, then Phase 2.
Phase 1: Codebase Investigation
Decide which repo owns the backend implementation. Node ownership (which workflow nodes live in dify vs graphon) is maintained in one place: .claude/skills/dify-docs-feature-research/references/detection-tables.md. Read that file to route the feature; do not route from memory.
Human Input is split across both repos: graphon executes the node (src/graphon/nodes/human_input/), while dify owns the boundary, callback, and session-binding code (api/core/workflow/nodes/human_input/). Research both halves.
Locate the code:
Layer
Repo
Path
Workflow node backend
per ownership table (step 1)
graphon: src/graphon/nodes/<node_name>/ or dify: api/core/workflow/nodes/<node_name>/
Graph engine, runtime state, variable pool, command channels, layers
graphon
src/graphon/graph_engine/, src/graphon/runtime/
Model runtime, model providers, LLM/embedding/rerank invocation
graphon
src/graphon/model_runtime/
Workflow orchestration in Flask routes and Celery tasks
dify
api/controllers/, api/tasks/, api/services/
RAG and knowledge retrieval logic
dify
api/core/rag/
Tool plugins
dify
api/core/tools/
Frontend UI (all features; the web app was never split out)
dify
nodes: web/app/components/workflow/nodes/<node-name>/ (kebab-case); other features: web/app/components/<area>/
Permission-gated behavior (RBAC/ACL): the effective gate is here — read the capability map (web/utils/permission.ts: getAppACLCapabilities / getDatasetACLCapabilities) and the UI that consumes it (e.g. a canEdit → read-only hook), and confirm it in a test environment. A backend @rbac_permission_required decorator can be looser than the frontend and never fire, so treat it as a lower bound. Permission labels for docs: web/i18n/{en-US,zh-Hans,ja-JP}/permission-keys.json.
Trace the API surface: how the feature's output reaches the API response. Check controllers, response converters, and serialization (all in dify).
Coverage gate — account for every surface before concluding. What users experience is the composition of backend + frontend + configuration; a conclusion read off a single surface is not a finding. A backend permission decorator can be looser than the frontend gate and never fire; a frontend option can be dead without its backend flag; a shipped default can disable the code path you just read. For each surface — backend, frontend UI, i18n labels, feature flags / env defaults, API, plugin SDK (plugin-facing features only) — record the files read, or N/A plus why that surface cannot affect this feature. Carry the filled table into the Phase 3 summary.
Produce a summary of:
What the feature does (based on code, not existing docs)
What configuration options exist
What data types / values are supported
How results are returned to the user (UI, API, streaming)
Any notable edge cases or limitations visible in the code
Search for user-reported problems and questions across these channels:
GitHub Issues — Run multiple searches with varied terms. Always search dify; also search graphon when the feature is a built-in workflow node, the graph engine, runtime, or model_runtime:
bash
gh issue list --repo langgenius/dify --search "<feature name>" --limit 30 # e.g. "human input"
gh issue list --repo langgenius/dify --search "<alternative name>" --limit 30 # e.g. "HITL"
gh search issues "<feature> <context>" --repo langgenius/dify --limit 20 # e.g. "human input timeout"
# For built-in nodes, engine, runtime, or model_runtime, also:
gh issue list --repo langgenius/graphon --search "<feature name>" --limit 30
gh search issues "<feature> <context>" --repo langgenius/graphon --limit 20
End users typically file in dify even for graphon-owned behavior; graphon's tracker tends to hold engineering-side reports. Check both to avoid missing pain points.
GitHub Discussions — Search for related discussion topics. <pattern> is a case-insensitive regex, e.g. "human ?input":
bash
gh api "repos/langgenius/dify/discussions?per_page=30" --jq '.[] | select(.title | test("<pattern>"; "i"))'
For each relevant issue or discussion, read the body and top comments to understand:
What the user was trying to do
What went wrong or was confusing
Whether it's a bug, missing feature, or documentation gap
Categorize findings into:
Category
Description
Documentation gap
User couldn't find information that should be documented
Confusion
User misunderstood behavior the docs should clarify
Bug
Product defect — note but don't document workarounds as features
Feature request
Missing capability — note but don't document as existing
Phase 3: Synthesize
Combine both phases into a structured research record. It is research output, not the drafter's brief: at S3 the pipeline writes the summary the drafter gets from this record, in the shape dify-docs-write/references/research-summary.md gives.
## Feature: [Name]
### How It Works (from code)
- [Key behaviors, configuration options, supported types]
- [API response structure]
- [Edge cases or limitations]
- [Unverified inferences — flagged for user testing]
### Surface Coverage (from the Phase 1 coverage gate)
| Surface | Files read, or N/A + why |
|---------|--------------------------|
| Backend | ... |
| Frontend UI | ... |
| i18n labels | ... |
| Flags / env defaults | ... |
| API | ... |
| Plugin SDK | ... |
### Current Documentation
- [What the existing page covers]
- [What it's missing]
### Community Pain Points
| Theme | Issues | Type | Doc impact |
|-------|--------|------|------------|
| ... | #123 | gap | Should document |
### Recommended Documentation Scope
- [What to add based on gaps]
- [What to clarify based on confusion]
- [What to explicitly omit and why (bugs, unreleased features, UI-discoverable mechanics)]
Present the record to the user. STOP — do not start the writing phase until the user reviews the findings and confirms the scope. Under dify-docs-write with no reviewer in the session, that skill's rule applies: the record goes into the PR description and the run continues.
Important
This skill produces research only. Do not start writing documentation until the user reviews the findings and confirms the scope; under dify-docs-write with no reviewer in the session, that skill's rule applies.
Research findings exist to make the page's claims accurate, not to be exhaustively included. When recommending scope, apply the style guide's "Repeating the UI" filter: UI-discoverable mechanics stay out of the page unless especially consequential.
When scope is confirmed and writing begins, return to the dify-docs-write pipeline — it loads the doc-type rule pack and the writing guides. This skill carries none of the writing rules.
Flag code-inferred behavior as unverified. Ask the user to test before documenting as fact.
Distinguish bugs from documentation gaps. Documenting buggy behavior as intended causes more harm than leaving a gap.
Note issue numbers for traceability. The user may want to reference them when prioritizing what to cover.
Dify Docs Feature Research 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.
Dify Docs Feature Research compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
Dify Docs Feature Research this skilllanggenius/dify-docs
Reviews frontend changes under `web/` or `packages/dify-ui/` for concrete defects and broken project contracts, using routed rule packs and a severity scale for findings.
Use when implementing or refactoring React/TypeScript components and the task requires decisions about component ownership, feature boundaries, state, data…
Use when writing or changing Vitest or React Testing Library tests under `web/` or `packages/dify-ui/`, or when the user explicitly requests frontend test…
Audit terminology consistency across documentation against the codebase UI labels and the glossary — in prose and in the UI strings shown in screenshots.
Rule pack for the Service API specs ({en,zh,ja}/api-reference/openapiservice.json): spec conventions, app-type scoping, code-verification rules, and the audit machinery.
The entry point for writing or revising any documentation in this repo: user guides, deployment pages, plugin-dev pages, API specs, the env-var reference, CLI pages.
Judge a finished draft as the docs owner would: a fresh agent reads it against the style guide and the reference page in its genre, marks the sentences that fall short, and returns a ship verdict on…
Research a Dify feature before writing or optimizing documentation. Dify Docs Feature Research is an agent skill from langgenius/dify-docs. Research a Dify feature before writing or optimizing documentation.
When should I use Dify Docs Feature Research?
Dify Docs Feature Research fits situations like: starting any doc task that requires understanding a features implementation; user pain points; community feedback.
How do I install Dify Docs Feature Research in Claude Code?
Run `npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a claude-code`. Or copy the skill folder (.claude/skills/dify-docs-feature-research in langgenius/dify-docs) into .claude/skills/dify-docs-feature-research in your project. Claude Code loads it when a task matches its description.
How do I install Dify Docs Feature Research in Codex?
Run `npx skills add langgenius/dify-docs --skill dify-docs-feature-research -a codex`. Or copy the skill folder (.claude/skills/dify-docs-feature-research in langgenius/dify-docs) into .agents/skills/dify-docs-feature-research in your project. Codex loads it when a task matches its description.
Can I use Dify Docs Feature Research 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 langgenius/dify-docs --skill dify-docs-feature-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dify-docs-feature-research, .gemini/skills/dify-docs-feature-research, .github/skills/dify-docs-feature-research and .opencode/skills/dify-docs-feature-research in your project.
What does Dify Docs Feature Research need to run?
Going by SKILL.md and its folder, Dify Docs Feature Research needs the command-line tools its instructions call (gh). Our summary lists: Docker.
Does Dify Docs Feature Research access the network?
SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Dify Docs Feature Research 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 Dify Docs Feature Research use?
Dify Docs Feature Research is published under the CC-BY-4.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Dify Docs Feature Research use?
About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.
What are the alternatives to Dify Docs Feature Research?
Skills that share tags, products or a category with Dify Docs Feature Research: Frontend Code Review (langgenius/dify, 158k stars), Dify Component Writing Guide (langgenius/dify, 158k stars), Dify Command Line with difyctl (langgenius/dify, 158k stars) and Dify Frontend Testing (langgenius/dify, 158k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dify Docs Feature Research?
langgenius (a GitHub organization) maintains it in langgenius/dify-docs, which has 178 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 9, 2026.
Source: langgenius/dify-docs on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
