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/tx1207/hello-scholar/record-experimentnpx skills add Tx1207/hello-scholar --skill record-experimentgit clone --depth 1 https://github.com/Tx1207/hello-scholarWrote 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/tx1207/hello-scholar/record-experiment)<a href="https://agentmods.dev/skills/tx1207/hello-scholar/record-experiment"><img src="https://agentmods.dev/badge/skills/tx1207/hello-scholar/record-experiment.svg" alt="Measured on agentmods" 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 | $0.00073 | $0.01878 |
| Opus 5 | $0.00036 | $0.00939 |
| Sonnet 5 | $0.00015 | $0.00376 |
| Haiku 4.5 | $0.00007 | $0.00188 |
Grade A, and why
record-experiment 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 5d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Record experiment
Preserve material experiment provenance in one recoverable Run Record without delaying ordinary tests or small experiments. Keep experiment identity, execution evidence, and generated Indexes in their owners.
1. Classify the evidence boundary
Read references/status-and-fields.md before a Full record or terminal update. Decide record granularity before launching or writing.
| Decision | Use when | Completion |
|---|---|---|
| Full record | A clearly formal, costly, long-running, remote, or retained-evidence experiment; missing upstream provenance; or a durable derived report | One valid root Record contains reproducible prelaunch facts |
| Append event | The same Run gains a material status, path, metric, error, decision, or terminal-evidence change | One concise event preserves the new durable fact without redefining identity |
| No record | Ordinary code/tests, static checks, read-only queries, preparation, or a low-risk small experiment with no clear formal, cost, or retained-evidence signal | Run directly and state briefly why no durable Run was created |
Default to No record. Run ordinary tests, smoke checks, and low-risk small experiments directly. Do not create a Run merely because a command or file name contains eval, benchmark, inference, or experiment. Do not ask the user to classify ambiguous low-risk work. Ask only when unclear production data, irreversible operations, or significant cost changes the safety decision.
An unrecorded small experiment remains a temporary observation. If formal evidence is needed later, create a Record for a subsequent formal Run; do not backfill the earlier scratch experiment. An existing branch, temporary directory, or Worktree may provide isolation, but this Skill does not create a Worktree automatically.
Formal prelaunch record. Before a clearly formal/baseline/release Benchmark or Eval, full training, long-running or expensive GPU/remote job, retained checkpoints/predictions/results, or evidence for acceptance, publication, product decisions, external sharing, or downstream experiments, create a minimum reproducible Record. Missing an exact command, CWD, intended raw stdout/stderr paths, or intended result locations blocks launch.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 107 lines · 73 tokens per session scan A 97e72d27d461
record-experiment is a skill published in the GitHub repository Tx1207/hello-scholar (5 stars, last pushed 23d ago), licensed MIT. It adds 73 tokens to every session and 1,878 once invoked, about $0.0004 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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