Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add timjensgrossinger/threnody --skill threnody-swarmgit clone --depth 1 https://github.com/timjensgrossinger/threnodyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/timjensgrossinger/threnody/threnody-swarm)<a href="https://agentmods.dev/skills/timjensgrossinger/threnody/threnody-swarm"><img src="https://agentmods.dev/badge/skills/timjensgrossinger/threnody/threnody-swarm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/timjensgrossinger/threnody/threnody-swarm"><img src="https://agentmods.dev/badge/skills/timjensgrossinger/threnody/threnody-swarm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.01694 |
| Opus 5 | $0.00030 | $0.00847 |
| Sonnet 5 | $0.00012 | $0.00339 |
| Haiku 4.5 | $0.00006 | $0.00169 |
Grade A, and why
threnody-swarm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threnody swarm orchestration
Default: host-native swarms
For MCP host callers (Claude, Copilot, Cursor, Codex, etc.), execute_swarm
defaults to host_native:
- Threnody plans the task.
- Returns
awaiting_host_execution: true+host_spawn_waves. - You spawn host
Task/Agentper wave — Threnody does not subprocess.
This path is unaffected by utility-only delegation rules.
Fast-start contract
Agent-emitting swarm paths must return host_spawn_waves quickly: target
under 5 seconds to a spawnable handoff and under 30 seconds to first host
spawn. Use the fast host-native handoff first; optional refinement, consensus,
learning aggregation, and detailed receipts happen after the first worker wave
starts or at terminal reporting.
Within each wave, spawn every agent as the same batch before waiting on the wave barrier. A host loop that starts one same-wave agent, waits, then starts the next is a fast-start regression.
Token discipline applies to all swarm shapes: keep host-native handoff compact, prefer bounded file-level fanout for broad sweeps, and reserve star/consensus or high-tier synthesis for explicit deep-risk work.
Workflow
- If not already planned, follow
threnody-plan(plan-only swarm preview stops before spawn). - Optionally
route_taskfor tier context. execute_swarm(task, topology?, max_agents?, budget_limit?, workspace_root)— always passworkspace_root. Target paths are containment-checked against it; omit it and the server falls back to its own cwd and answers withworkspace_root_source: "cwd_fallback"plus aworkspace_root_warning.- Handle response:
awaiting_host_execution+host_spawn_waves— execute waves via host agents. The response carriesplan_summary, not a fullplanobject (all runs, not just review runs). Spawn fromhost_spawn_waves; readplan_summary.coveragefor file accounting — a non-emptycoverage.deferredmeans a named file has no owner, andcoverage.packedmeans the agent budget merged files into fewer agents. Full plan fidelity stays server-side (inspect_run_receipt).preview: true+preview_token— cost over budget; confirm then re-call with token.started: true(delegate mode only) — Threnody subprocess orchestrator running.- Check
learning_report_contract.report_mode(batchdefault, orinline).
- Reporting — depends on
report_mode:batch(default): Do NOT callreport_host_wavefor plain worker waves. Just spawn each wave natively. Per-agent learning is captured automatically (PostToolUse hook) or, whenlearning_capture=model, by passing the agents to the single terminal call. This is the fast path — no per-wave MCP round-trip.inline(legacy): callreport_host_waveafter each wave withworkspace_rootand per-agent results (task_id,spawn_id,success,touched_files,output_excerpt).
- Mid-run expansion (both modes): after scaffold/contract waves, call
expand_host_plan(discovered_files=[...])to spawn additional file-scoped agents. - Terminal: call
report_host_swarm_complete(outcome=accepted|revised|reworked|rejected)once at the end (inbatchmode this imports the whole run and finalizes). Ininlinemode you may instead setterminal=trueon the lastreport_host_wave. Verifyfinalize.swarm_outcome.stored. - Monitor:
- Host-native:
inspect_swarmfor status; optionalinspect_status. - Delegate:
list_subtasks,resume_swarm_inspect,resume_swarm_confirm.
- Host-native:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 139 lines · 60 tokens per session scan A 74511a424def
threnody-swarm is a skill published in the GitHub repository timjensgrossinger/threnody (2 stars, last pushed 14d ago), licensed Apache-2.0. It adds 60 tokens to every session and 1,694 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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