docs-orchestrator
Skill4 starsChanged 4 months agoApache-2.0View on GitHub
Documentation workflow orchestrator. Reads the step list from .agent_workspace/docs-workflow.yaml (or the plugin default). Runs steps sequentially, manages progress state, handles iteration and confirmation gates. Claude is the orchestrator — the YAML is a step list, not a workflow engine.
- Reads credentials
1 other project uses a version of this.
Adopted by
Most recently taken up by
- Kanevry/session-orchestratortheir own version, first seen Oct 2, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- Kanevry/session-orchestrator★ 53same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository53 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- action-commentsSkill
- article-extractorSkill
- docs-convert-gdoc-mdSkill
- docs-review-content-qualitySkill
- docs-review-modular-docsSkill
- docs-review-securitySkill
- docs-review-styleSkill
- docs-review-technicalSkill
- docs-ticket-readinessSkill
- docs-workflow-code-analysisSkill
- docs-workflow-create-jiraSkill
- docs-workflow-create-merge-requestSkill
- docs-workflow-jira-readySkill
- docs-workflow-pipeline-diagnosticsSkill
- docs-workflow-planningSkill
- docs-workflow-pr-analysisSkill
- docs-workflow-quality-gateSkill
- docs-workflow-requirementsSkill
- docs-workflow-scope-req-auditSkill
- docs-workflow-security-reviewSkill
- docs-workflow-startSkill
- docs-workflow-style-reviewSkill
- docs-workflow-tech-reviewSkill
- docs-workflow-writingSkill
- git-pr-readerSkill
- ibm-sg-audience-and-mediumSkill
- ibm-sg-language-and-grammarSkill
- ibm-sg-legal-informationSkill
- ibm-sg-numbers-and-measurementSkill
- ibm-sg-punctuationSkill
- ibm-sg-referencesSkill
- ibm-sg-structure-and-formatSkill
- ibm-sg-technical-elementsSkill
- jira-readerSkill
- jira-writerSkill
- learn-codeSkill
- lint-with-valeSkill
- mdita-writeSkill
- query-codeSkill
- redhat-docs-tocSkill
- rh-ssg-accessibilitySkill
- rh-ssg-formattingSkill
- rh-ssg-grammar-and-languageSkill
- rh-ssg-gui-and-linksSkill
- rh-ssg-legal-and-supportSkill
- rh-ssg-release-notesSkill
- rh-ssg-structureSkill
- rh-ssg-technical-examplesSkill
- rn-known-issuesSkill
- understand-pull-requestSkill
- validate-plugin-prereqsSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
13 rules. About 0 are common, 3 are distinctive, and 10 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 24
Do not source .env files or check for tokens/CLIs — downstream scripts handle their own prerequisites.
- Distinctive: line 28
If the ticket argument is missing, STOP and ask the user.
- Very specific: line 50
Read the JSON action field and act:
- Distinctive: line 58
After the skill completes, report the result:
- Very specific: line 64
If the skill failed (threw an error, produced no output), add --failed:
- Very specific: line 77
Run the prepare command with Bash and parse the JSON response.
- Very specific: line 83
Run each command in the most recent response's finalize array with Bash.
- Very specific: line 90
Add --failed if verification failed in step 4, or if a dispatched primary agent errored or produced no output.
- Very specific: line 118
If a step is marked failed (halting the workflow) but the underlying cause has been fixed — or a step is stuck in a non-runnable state — …
- Very specific: line 130
Synchronous primary agents: When a step skill instructs you to dispatch an Agent, pass run_in_background: false for the step's primary …
- Distinctive: line 132
No stub results: If you cannot invoke a step's skill (e.g., context compaction removed its instructions), dispatch the step via an Agent …
- Very specific: line 136
Commit confirmation gate: Before the create-merge-request step, ask the user to confirm.
- Very specific: line 140
Every step writes to .agent_workspace/<ticket>/<step-name>/.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Docs Orchestrator
When the user invokes /docs-orchestrator, run THIS skill directly. Do NOT redirect to docs-workflow-start or any other skill.
The Python state machine driver owns all orchestrator logic. Claude calls the driver, parses JSON actions, and executes them.
Pre-flight
Install the workflow completion Stop hook (safe to re-run):
bash ${CLAUDE_SKILL_DIR}/scripts/setup-hooks.shDo not source .env files or check for tokens/CLIs — downstream scripts handle their own prerequisites.
Initialize
If the ticket argument is missing, STOP and ask the user.
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py init <TICKET> \
[--workflow <name>] \
[--pr <url>...] \
[--source-code-repo <url-or-path>...] \
[--no-source-repo] \
[--auto-discover-repos] \
[--max-secondary-repos <N>] \
[--mkdocs] \
[--draft] \
[--docs-repo-path <path>] \
[--create-merge-request] \
[--create-jira <PROJECT>] \
[--plugin-root ${CLAUDE_PLUGIN_ROOT}]The script handles argument parsing, source resolution, workflow YAML loading, progress file creation or resume, and step classification. It emits a single JSON action to stdout. Parse it and enter the action loop.
Action loop
Read the JSON action field and act:
run_skill
The response contains skill, args, step, message, and optional warnings and messages arrays.
- Display
message. Display anywarnings(prefix with WARNING) andmessages. - Invoke:
Skill: <skill>, args: "<args>" - After the skill completes, report the result:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py step-done <TICKET> <step>If the skill failed (threw an error, produced no output), add --failed:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py step-done <TICKET> <step> --failed- Parse the new JSON response and loop back to the action check.
dispatch
The response contains step, message, prepare (a shell command), and optional warnings and messages. This step is dispatched by the main loop via subagents instead of the Skill tool — subagents cannot dispatch other subagents, so only the main conversation can do this.
- Display
message. Display anywarnings(prefix with WARNING) andmessages. - Run the
preparecommand with Bash and parse the JSON response. It containsagents,post_commands,finalize,verify, andnext_phase. - Repeat while the current response has a non-empty
agentsarray: a. Dispatch each agent with the Agent tool:subagent_type= agenttype,prompt,description,run_in_background= agentbackground. Passmodelandschemaonly when they are non-null. If the array has more than one agent, dispatch them all in a single message so they run in parallel. b. Run each command in the response'spost_commandsarray (if any) with Bash. c. Ifnext_phaseis not null, run it with Bash, parse the new JSON as the current response, and go back to step 3a. Otherwise leave the loop. - Using the most recent response: if
verifyis set, check that file exists. If it is missing, plan to add--failedto the step-done call. - Run each command in the most recent response's
finalizearray with Bash. - Report the result:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py step-done <TICKET> <step>Add --failed if verification failed in step 4, or if a dispatched primary agent errored or produced no output.
- Parse the new JSON response and loop back to the action check.
complete
Display message and the summary object (completed steps, MR/PR URL, JIRA URL, module/file counts). Display any warnings. The workflow is done.
fail
Display message and reason. Display any warnings. Stop.
Querying status
To check workflow status without advancing it:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py status <TICKET>To get the next action without recording a step-done:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py next <TICKET>Recovery
If a step is marked failed (halting the workflow) but the underlying cause has been fixed — or a step is stuck in a non-runnable state — reset and retry it without hand-editing the progress JSON:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/docs_orchestrator.py retry-step <TICKET> <step>This resets the step to in_progress, un-fails the workflow, restores the active marker, and emits that step's action so the loop re-runs it. Handle the emitted action exactly as in the action loop above.
Guardrails
Rules the script cannot enforce — Claude must follow these during execution:
- Synchronous primary agents. When a step skill instructs you to dispatch an Agent, pass
run_in_background: falsefor the step's primary agent (the one whose output file the step verifies). Fan-out agents within a step may remain background. - No stub results. If you cannot invoke a step's skill (e.g., context compaction removed its instructions), dispatch the step via an Agent subagent in a fresh context or mark it failed. Never write a placeholder
step-result.jsonor mark a stepcompletedwith generic text. - Pipeline diagnostics via Agent. The
pipeline-diagnosticsstep runs last after 10+ skill invocations. Context compaction will have removed its skill instructions. Always dispatch it via the Agent tool in a fresh context. - Commit confirmation gate. Before the
create-merge-requeststep, ask the user to confirm. Show: branch name, target repo, file count. If declined, callstep-done <TICKET> create-merge-request --failed.
Output conventions
Every step writes to .agent_workspace/<ticket>/<step-name>/. See output and state reference for the folder structure and step-result schema for sidecar format.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

