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-plangit 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-plan)<a href="https://agentmods.dev/skills/timjensgrossinger/threnody/threnody-plan"><img src="https://agentmods.dev/badge/skills/timjensgrossinger/threnody/threnody-plan/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-plan"><img src="https://agentmods.dev/badge/skills/timjensgrossinger/threnody/threnody-plan.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 | $0.00052 | $0.01560 |
| Opus 5.5 | $0.00021 | $0.00624 |
| Sonnet 5.5 | $0.00010 | $0.00312 |
| Haiku 4.5 | $0.00005 | $0.00156 |
Grade A, and why
threnody-plan 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 1mo 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threnody planning mode
Unified planning entry point for normal orchestration (plan_task) and
swarms (execute_swarm). Every path ends at the same confirmation gate (§4) —
the difference between plan-only and plan-then-execute is only what the
recommended option is, not whether the user gets asked.
Trigger phrases
Plan-only: "plan only", "dry run", "show waves", "preview the swarm", "don't execute yet", "what agents would you spawn" — recommend Cancel at the gate and stop there unless the user picks a run option.
Plan-then-execute: default when user asks to build/implement/refactor without plan-only qualifiers — recommend the matching run option at the gate.
Always plan first: multi-file, multi-concern, or parallel agent work
Host-native plans auto-fan out to one agent per file when intent implies a webapp/fullstack stack (heuristic_intent_templates). Use expand_host_plan after scaffold waves if more files appear.
For broad code review, prefer the token-cheap FAST_REVIEW: shape (one
read-only reviewer per file plus synthesis). Use the deeper REVIEW: file ×
dimension swarm only when the user explicitly asks for deep review,
security-critical audit, threat modeling, or a named specialist dimension.
Fast-start contract
Any plan path that emits agents must return a spawnable host_spawn_waves
handoff quickly: target under 5 seconds to handoff and under 30 seconds
to first host spawn. Keep optional LLM refinement, consensus, detailed receipts,
and learning aggregation off the first-spawn path.
When executing a returned plan, spawn all agents in the same wave as one batch before waiting at the wave barrier. Never serialize agents inside a single wave.
Workflow
1. Classify
Call route_task(task=...) (MCP: Threnody).
2. Choose planning tool
| Need | Tool |
|---|---|
| Standard multi-step work, no swarm persistence | decompose_task (preferred) or plan_task |
Budget cap, swarm_id, topology, resume |
execute_swarm (host-native default) |
| Frontend + backend + API in parallel | Same tools + contract-first prompt (see threnody-fullstack) |
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.
- 1mo ago First seen · 158 lines · 52 tokens per session scan A d4ad5f8eb1b8
threnody-plan is a skill published in the GitHub repository timjensgrossinger/threnody (2 stars, last pushed 21d ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,560 once invoked, about $0.0002 per session on Opus 5.5. 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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