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 whenpoem/aiscientist --skill replaygit clone --depth 1 https://github.com/whenpoem/aiscientistWrote 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/whenpoem/aiscientist/replay)<a href="https://agentmods.dev/skills/whenpoem/aiscientist/replay"><img src="https://agentmods.dev/badge/skills/whenpoem/aiscientist/replay.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 5.1 | $0.00054 | $0.00449 |
| Opus 5 | $0.00027 | $0.00225 |
| Sonnet 5 | $0.00011 | $0.00090 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
replay 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 7d 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.
What it actually says
Replay
Replay is an inspection over frozen state. It does not execute new experiments and must not modify live graph nodes, ratings, judgments, or preregistrations.
Workflow
- If the user did not provide a snapshot id, call
mcp__memory__list_snapshots(limit=20). Show label, timestamp, and counts; do not create a new snapshot merely to replay the past. - Phrase exactly one counterfactual in a falsifiable sentence, such as
Approve hyp_07 instead of pausing it. - Call
mcp__memory__replay_counterfactual(snapshot_id, counterfactual)and retain the returnedbranch_id. - Inspect only the recorded snapshot and branch metadata. Do not call model
scripts,
seed_perturb, or the sequestered-data query tool. - If the analysis suggests a live action, report it as a recommendation. The
user may later call
resume_branch; replay itself never flips status.
Output shape
Return:
snapshot_id: <snap_...>
branch_id: <replay_...>
counterfactual: <one sentence>
live_graph_mutated: false
evidence: <recorded facts used>
finding: <what changes under the counterfactual>
recommendation: <none or explicit user action>
limitations: <what replay cannot establish without a new experiment>
For several what-ifs, create one replay branch per counterfactual and keep each
output independent. Use mcp__memory__list_replay_branches(limit=20) to audit
existing branches before adding duplicates.
Completion criteria
Replay is complete when the source snapshot and new branch are identifiable, the live graph is unchanged, every finding cites recorded snapshot evidence, and any proposed live change is clearly left for separate user approval.
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.
- 7d ago First seen · 49 lines · 54 tokens per session scan A 6368d12647bb
replay is a skill published in the GitHub repository whenpoem/aiscientist (8 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 449 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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