AutoSci is an AI research platform organized around a wiki, with an agent that supports stages of scientific work such as reading, experimentation, writing, and retaining knowledge across projects. It is for people building or using AI-assisted research workflows, with Claude Code, Codex, and OpenCode adaptations available. The catalogue add-ons extend those agent-specific workflows.
Borrowing it
Nothing to install: this file belongs to skyllwt/AutoSci. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/skyllwt/AutoSci/main/.claude/skills/hiera-experiment/SKILL.mdgit clone --depth 1 https://github.com/skyllwt/AutoSciWrote 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/skyllwt/autosci/hiera-experiment)<a href="https://agentmods.dev/skills/skyllwt/autosci/hiera-experiment"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/hiera-experiment/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/skyllwt/autosci/hiera-experiment"><img src="https://agentmods.dev/badge/skills/skyllwt/autosci/hiera-experiment.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 | $0.00025 | $0.04120 |
| Opus 5.5 | $0.00010 | $0.01648 |
| Sonnet 5.5 | $0.00005 | $0.00824 |
| Haiku 4.5 | $0.00003 | $0.00412 |
Grade A, and why
hiera-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 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 — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/hiera-experiment
Purpose and activation boundary
Use this skill only after the user explicitly selects the optional Hiera path for an existing AutoSci experiment. Hiera is an isolated search sidecar:
- It reads the linked wiki experiment/design and runtime contract as inputs.
- It stores all Hiera state below runs/hiera///.
- It searches immutable candidate snapshots and records evidence in the sidecar ledger.
- It never creates wiki entities, changes wiki schema or experiment status, rewrites wiki/log.md, or writes search results back to the wiki.
- It does not replace /exp-design, /exp-run, /exp-eval, or /research. A confirmatory result must return to the normal, user-gated workflow.
Before creating or changing a run, read:
- README.md for the user-facing sequence and command examples.
- references/interface.md for contract fields, source layouts, and remote receipts.
- The relevant runtime contract files when a field or permission is unclear.
Never infer a method, metric direction, resource boundary, seed policy, or remote environment from a vague request. Ask for the missing decision or ask the user to provide a text constraint.
State model and command ownership
Treat the lifecycle as a state machine, not as one automatic command:
init
-> inspect/complete semantic_space and task_contract
-> propose semantic points
-> author drafts and candidate specs
-> admit immutable candidates
-> explicit human source/contract review
-> approve frozen contract
-> preflight
-> run(screen)
-> choose one iteration branch:
propose a new semantic direction
tune reviewed config_schema children
loop existing candidates at deep depth
status/recover pending remote attempts
-> finalize sidecar report
-> optional formal confirmation through /exp-run and /exp-eval
The CLI subcommand and the agent action are different:
| Stage | CLI command | Agent-owned action |
|---|---|---|
| Initialize | init | Create the sidecar and show readiness errors. |
| Complete inputs | none | Edit only user-confirmed semantic or contract inputs; validate them. |
| Propose | propose | Show point IDs and metadata; do not create source. |
| Author | none | Write reviewed source/spec under this run's drafts; do not call propose again. |
| Admit | admit | Import exactly the reviewed draft into an immutable snapshot. |
| Approve | approve | Run only after explicit human approval of the execution boundary. |
| Preflight | preflight | Check a candidate without reserving evaluation budget. |
| Evaluate | run | Execute one immutable snapshot at screen or deep depth. |
| Tune | tune | Create and evaluate bounded immutable config children. |
| Loop | loop | Schedule deep bouts among existing eligible candidates only. |
| Observe/recover | status / recover | Poll or reconcile an existing remote attempt; never resubmit it. |
| Finalize | finalize | Write the exploratory sidecar report only. |
What ships with it
2 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.
- 1mo ago First seen · 345 lines · 25 tokens per session scan A 00ae10f316d6
hiera-experiment is a skill published in the GitHub repository skyllwt/AutoSci (1,706 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 4,120 once invoked, about $0.0001 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 2026-09-29.
hiera-experiment compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| hiera-experimentskyllwt/AutoSci | Skill | 1.7k | 1mo ago | MIT | A | 25 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | today | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |