بنقرة واحدة
ponder-forge-usage
Operate Ponder-Forge complex-problem workflows through the pure CLI.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Operate Ponder-Forge complex-problem workflows through the pure CLI.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| 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.