research-workflow-orchestrator
Skill67 starsChanged 7 months agoMITView on GitHub
Run a resumable end-to-end research workflow that automates low-risk work, pauses at explicit human decision gates, records provenance, and routes each stage to the appropriate research-hub skill or MCP tool.
In this repository14 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- research-hubSkill
- gap-to-topicSkill
- literature-triage-matrixSkill
- notebooklm-brief-verifierSkill
- paper-memory-builderSkill
- paper-summarizeSkill
- research-context-compressorSkill
- research-design-helperSkill
- research-hub-multi-aiSkill
- research-hubSkill
- research-project-orienterSkill
- zotero-library-curatorSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. About 0 are common, 10 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈10
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 28
Do not use for one isolated operation.
- Very specific: line 35
Read ../research-hub/references/research-protocol.md for the scope-to-query map, literature roles, version/decision observations and …
- Distinctive: line 39
Do not infer substantive coverage from a candidate count or command exit.
- Distinctive: line 40
If shared files are unavailable, preserve user constraints, actual source level, load-bearing evidence gaps and planned/executed …
- Very specific: line 51
If the state file does not exist, propose a workflow ID and start at orient.
- Distinctive: line 83
no gate: execute and validate.
- Distinctive: line 87
Write state atomically; never record success before validation passes.
- Distinctive: line 88
Advance: only when exit criteria in the workflow contract pass.
- Distinctive: line 134
Do not synthesize claims from unverified metadata or treat a NotebookLM brief as ground truth.
- Very specific: line 148
Keep pending_action specific enough to resume, but never include API keys, cookies, OAuth tokens, or secrets.
- Distinctive: line 150
If current bytes, dependencies, or time-sensitive inputs differ from the recorded evidence, rerun only the smallest affected validation.
- Distinctive: line 159
Never silently switch data sources, models, research questions, or inclusion criteria.
- Distinctive: line 161
Never treat an unavailable MCP tool as permission to perform a broader browser or shell mutation.
- Distinctive: line 179
Use the domain service through either interface.
- Very specific: line 186
All CLI operations accept --json.
≈ “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
research-workflow-orchestrator
Coordinate an entire research project without turning consequential scientific
decisions into silent automation. The orchestrator resumes from
.research/workflow_state.yml, performs safe work automatically, and asks for
one structured decision only when the next action crosses a declared gate.
This is a coordination skill, not a new research engine. It routes to the
existing research-hub skills and available CLI/MCP integrations. Read
references/workflow-contract.md before the first run. Read
references/tool-adapters.md only for the current stage or when selecting a
tool adapter. The machine-readable state contract is
references/workflow-state.schema.json.
Use when
- The user asks to run, resume, automate, or supervise a multi-stage research project.
- Work spans at least three of topic scoping, discovery, synthesis, design, experiments, writing, and release.
- A persistent human-in-the-loop audit trail is required.
Do not use for one isolated operation. Route a single literature table to
literature-triage-matrix, one design conversation to
research-design-helper, one paper summary to paper-summarize, or project
orientation alone to research-project-orienter.
Shared research contract
Read ../research-hub/references/research-protocol.md for the scope-to-query
map, literature roles, version/decision observations and bounded completion;
read ../research-hub/references/source-claim-audit.md for source support.
Native research remains available when Hub runtime/actions are unavailable.
Do not infer substantive coverage from a candidate count or command exit.
If shared files are unavailable, preserve user constraints, actual source level,
load-bearing evidence gaps and planned/executed distinctions explicitly.
Required inputs
- Project root.
- User objective and constraints.
- Existing
.research/manifests, if present. - Available tool capabilities. Discover them; never assume an MCP server, connector, credential, or browser session exists.
If the state file does not exist, propose a workflow ID and start at orient.
Creating the local state file is reversible, but present the initial plan before
executing later stages.
Automation policy
Classify every proposed action before invoking a tool:
| Action class | Default behavior |
| Read-only discovery, validation, comparison | Run automatically |
| Local deterministic generation with a preview or rollback | Run automatically, preserve provenance |
| Local reversible metadata update | Run automatically when inside approved scope |
| External write, public communication, account change | Stop at external_write |
| Costly or long experiment/simulation | Stop at experiment_authorization |
| Semantic manuscript/rebuttal change | Stop at semantic_revision |
| Submission, publication, release, merge, destructive cleanup | Stop at release_authorization |
Unknown risk is gated. Tool availability never lowers the gate class.
Run loop
- Load
.research/workflow_state.ymland validate the fields used by the current run. If absent, initialize from the schema; do not invent completed decisions or artifacts. - Orient with
research-project-orienter, or create a previewed local manifest usingresearch-context-compressorafter presenting the initial plan. This reversible project-local initialization needs no separate gate; freezing its research question or scope still needsscope_commitment. - Plan the smallest next stage. Name inputs, expected artifacts, tool adapter, validation, risk class, and any gate.
- Decide:
- no gate: execute and validate;
- gate: show the decision packet and wait;
- missing capability: use the documented fallback or report a blocker.
- Record stage, action, hashes/provenance, validation result, and decision. Write state atomically; never record success before validation passes.
- Advance only when exit criteria in the workflow contract pass. Otherwise retry within the declared bound or stop with a concrete blocker.
- Resume from the recorded pending action. Never rerun a costly or external action merely because a new chat/session started.
Human decision packet
At a gate, present only what the researcher needs to decide:
Gate: <gate id>
Decision: <one sentence>
Why now: <evidence and uncertainty>
Proposed action: <tool + exact mutation/cost/scope>
Preview: <diff, plan, candidates, or artifact link>
Reversible: <yes/no and rollback>
Options: accept / decline / revise / cancelaccept: record approval for the exact action and scope, then continue.decline: record the decision, choose a safe alternative if one exists, and do not repeatedly ask for the same rejected action.revise: block execution until a replacement action with a new hash is presented and accepted.cancel: record cancellation and stop the workflow cleanly.
An accept is valid only through a signed policy checkpoint or exact local-TTY
hash confirmation. A bare actor label from an agent or MCP caller is not human
authorization.
Approval is scoped to the described action. A later public, destructive, more expensive, or semantically different action needs a new decision.
Stage routing
| Stage | Primary routes | Required evidence before advancing |
orient | research-project-orienter, research-context-compressor | project manifest and open questions |
scope | gap-to-topic, research-design-helper | accepted question, criteria, constraints |
discover | literature-triage-matrix, research-hub search, Zotero | need-to-query coverage and actual outcomes, deduplicated candidate set, unresolved scope/access limits |
synthesize | paper-summarize, paper-memory-builder, NotebookLM verifier | version/source-level claim-evidence map, assessed/total claims, contradictions and unassessed gaps |
design | research-design-helper | design dossier and explicit assumptions |
execute | project-specific code/experiment tools | reproducible command, outputs, validation |
write | academic writing skill chain | source-linked draft and review findings |
release | verification, Git/GitHub/submission tools | release checklist and human authorization |
Do not synthesize claims from unverified metadata or treat a NotebookLM brief as ground truth. Do not invent missing sources, results, approvals, or tool output.
State and provenance
- Canonical state path:
.research/workflow_state.yml. - Store artifact paths plus SHA-256, stage, and timestamp. Do not store artifact contents in state.
- Store action IDs, exact scope, parameter/preview hashes, resource bounds, and decision summaries—not private deliberation or credentials. Execute an accepted action only when these machine-verifiable fields still match.
- Store every attempt and validation result in
actions[]; terminalcompleted/cancelledstates have no pending action, andcancelledmust include acanceldecision. - Keep
pending_actionspecific enough to resume, but never include API keys, cookies, OAuth tokens, or secrets. - If current bytes, dependencies, or time-sensitive inputs differ from the recorded evidence, rerun only the smallest affected validation.
Failure behavior
- Bound retries per action; default maximum is two attempts unless the plan declares a smaller limit.
- On repeated failure, set status to
blocked, preserve the last verified artifact, and report the exact recovery condition. - Never silently switch data sources, models, research questions, or inclusion criteria.
- Never treat an unavailable MCP tool as permission to perform a broader browser or shell mutation.
Completion output
Return:
- current stage and status;
- completed stages and validated artifacts;
- human decisions and their scope;
- unresolved evidence gaps or blockers;
- exact next action, or
nonewhen complete.
The workflow is complete only when the release exit criteria pass or the user
explicitly ends the project. A draft alone is not completion.
Executable runtime
Use the domain service through either interface; both paths make the same state transition:
- CLI:
research-hub workflow init|status|validate|decide|resume|migrate - MCP:
workflow_initialize,workflow_status,workflow_validate,workflow_decide,workflow_resume, andworkflow_migrate
All CLI operations accept --json. Migration is a dry run unless --apply
is given; apply creates a backup and atomically replaces the state. Schema 1.0
remains readable, while decisions and resume require migration to schema 1.1.
The optional agent-collab-harness v0.4 policy/checkpoint layer is discovered
at runtime. If no policy is configured, research-hub keeps its standalone
behavior. If a policy is configured but the package, policy, or checkpoint is
unavailable, resume fails closed. research-hub doctor --json reports the
integration as available, unavailable, or misconfigured.
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.

