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 agentmods add skills/emaballarin/ccplugins/roundnpx skills add emaballarin/ccplugins --skill roundgit clone --depth 1 https://github.com/emaballarin/ccpluginsWhat 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 | $0.00173 | $0.01360 |
| Opus 5 | $0.00086 | $0.00680 |
| Sonnet 5 | $0.00035 | $0.00272 |
| Haiku 4.5 | $0.00017 | $0.00136 |
Grade A, and why
round 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 2d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/tml:round — design the next experiment
Turn a question into a study whose answer will actually mean something. The whole value is in two things: one goal, and an honest scientific / nuisance / fixed split. Everything else is bookkeeping.
First action, always
ls -la ./.tml/rounds/ 2>/dev/null | tail -5; cat ./.tml/frontier.md 2>/dev/null | head -40
Number this round after the highest existing one. If earlier rounds exist, read the most recent spec and its verdict — a round that repeats a settled question is wasted budget, and a round that ignores the previous round's caveats inherits them silently.
Hard rules
- One goal per round. If the goal needs an "and", it is two rounds. Two simultaneous questions cannot be disentangled afterwards.
- Write the role assignment down. A round whose scientific / nuisance / fixed
split was never recorded cannot be checked for fairness later — and it will
be, by
/tml:analyze, possibly in a different session. - Every fixed hyperparameter is a caveat on the conclusion. Record it as one, in those words.
- Never put
max_train_stepsin the search space. Fixed per study. - Read-first. Writes only under
./.tml/rounds/NNN/. Never runs training.
Procedure
1. Establish the regime — before designing anything
references/regime.md. Three questions: how many trials can run concurrently,
where do they run, and does this plugin get to see the results directly. The
answers change the design, not just its execution. Do not guess the trial
capacity from device count.
2. Scope the goal
One sentence. references/study-design.md §1. Then state plainly whether this
round is exploration (insight — the default and the majority) or
exploitation (a best configuration). They use different samplers and have
different success criteria.
3. Assign roles
references/hyperparameter-roles.md. In order:
- Name the scientific hyperparameters — usually one.
- Everything else starts nuisance.
- Demote nuisance → fixed deliberately, under budget pressure, preferring the ones that interact least with the scientific hyperparameters. Record each caveat.
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.
- 2d ago First seen · 118 lines · 173 tokens per session scan A 5c7a4f7c45f2
round is a skill published in the GitHub repository emaballarin/ccplugins (3 stars, last pushed 26d ago), licensed MIT. It adds 173 tokens to every session and 1,360 once invoked, about $0.0009 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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