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Operate Ponder-Forge complex-problem workflows through the pure CLI.
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Baseado na classificação ocupacional SOC
| name | ponder-forge-usage |
| description | Operate Ponder-Forge complex-problem workflows through the pure CLI. |
| version | 0.2.0 |
| author | Hermes Agent |
Use Ponder-Forge for complex problems that need multiple child agents, structured evidence, independent review, gate checks, and graph-backed finalization.
Ponder-Forge is intentionally operated as a skill + CLI workflow. The installed workflow exposes no Ponder-Forge direct model tools or hooks; use native Hermes delegate_task for child execution and the Ponder-Forge CLI for state transitions.
Use the installed plugin CLI path for normal user-facing work:
PF_CLI="${HERMES_HOME:-$HOME/.hermes}/plugins/ponder_forge/cli.py"
For source-tree development only, use the repository-local cli.py.
Start a run. Omit --budget-json for the default 8x4 swarm, or pass positive integer budget keys explicitly:
python3 "$PF_CLI" start --goal "<complex problem>" --profile auto --budget-json '{"top_level_runs": 8, "child_concurrency_per_lane": 4}'
Plan tasks:
python3 "$PF_CLI" plan --run-id <run_id>
plan creates queued lane coordinator tasks plus planned lane-child backlog rows. top_level_runs controls the number of top-level lane coordinators. child_concurrency_per_lane is the maximum number of child subagents a lane coordinator may have in flight at once; it does not cap the total planned child backlog.
Produce native delegation payloads for lane coordinators:
python3 "$PF_CLI" delegations --run-id <run_id>
The parent/controller calls native Hermes delegate_task with the returned delegate_task_payload. Lane coordinator payloads use native role="orchestrator".
Each lane coordinator calls native delegate_task for only the child tasks in its manifest. Run repeated child waves with at most child_concurrency_per_lane child subagents in flight at once. The lane coordinator then returns one lane report JSON with child_reports.
The parent/controller submits each lane report through the CLI:
python3 "$PF_CLI" submit-report --file <report.json>
The lane report JSON must include run_id, the lane coordinator task_id, role, summary, child_reports, assertions, and artifacts. Prefer the exact lane report contract embedded in delegations output; it contains the active profile's critical assertion type and gate-required evidence groups.
Lane report contract for manual delegations:
{
"run_id": "<run id>",
"task_id": "<lane coordinator task id>",
"role": "swarm_lane_coordinator",
"summary": "lane-level synthesis",
"child_reports": [
{
"task_id": "<planned child task id>",
"role": "<planned child role>",
"summary": "short evidence-backed child summary",
"assertions": [
{
"assertion_type": "<profile critical assertion type; never leave this placeholder literal>",
"text": "claim to preserve in final reasoning",
"importance": 0.9,
"critical": true,
"confidence": 0.8,
"evidence": [
{
"evidence_type": "<profile evidence type>",
"source_ref": "path or command source",
"quote_or_observation": "observed value or output",
"command": "exact command if applicable",
"exit_code": 0
},
{"evidence_type": "<another required profile evidence type>", "source_ref": "path", "quote_or_observation": "consistency check"}
]
}
],
"artifacts": [
{"artifact_type": "report", "path": "path/to/report.md", "summary": "what it contains"}
]
}
],
"assertions": [],
"artifacts": []
}
Children return child JSON to their lane coordinator. Lane coordinators return one lane report to the parent/controller. Neither child agents nor lane coordinators call the Ponder-Forge CLI; the parent/controller submits reports and records verdicts. Profile anchors: research uses factual_claim; coding uses code_claim with root_cause_trace plus successful passing_test or execution_log with exit_code=0; design uses design_decision; analysis uses data_result with metric_output.command and exit_code=0; math uses proof_step plus critique or proof_check and only positive/unresolved counterexample evidence blocks.
Inspect status until the swarm topology is complete:
python3 "$PF_CLI" status --run-id <run_id>
status.swarm reports lane count, child backlog count, finished lane/child counts, queued delegation count, and incomplete task count. If next_required_action is delegations, call delegations and native delegate_task; if it is submit-report, submit missing lane reports.
Run independent review or record a verdict after lane and child reports are submitted:
python3 "$PF_CLI" verify --run-id <run_id> --mode independent_review --target-id <assertion_id>
python3 "$PF_CLI" verify --run-id <run_id> --mode independent_review --target-id <assertion_id> --reviewer-task-id <task_id> --independent-from-task-id <producer_task_id> --verdict accept --confidence 0.9 --rationale "<why>"
The first command creates reviewer tasks and may return a delegate_task_payload_suggestion; call native delegate_task with that payload, then record each reviewer verdict with the returned reviewer task id and the original producer task id.
Check the gate:
python3 "$PF_CLI" gate --run-id <run_id>
Finalize only when the gate allows it:
python3 "$PF_CLI" finalize --run-id <run_id>
python3 "$PF_CLI" reconcile --run-id <run_id>
status.next_required_action="complete" is terminal. If tasks are still queued or reports are missing, use delegations --run-id <run_id> and native delegate_task; use reconcile for stale running/orphan tasks and follow any returned retry payload.
finalize returns a final report.delegate_task only for child execution; use the Ponder-Forge CLI for Ponder-Forge state transitions.success=false as a blocker and fix the cause before continuing.