| name | experiment-log-interview |
| description | Conducts a structured Socratic interview to produce or update a single experiment log entry — the durable record of what was run, what it showed, and what it means. Use this skill whenever the user wants to log an experiment, write up results, record a backtest, capture a finding, pre-register a run, document a study, or update an existing entry with new results or a revised interpretation. Trigger on phrases like "log this experiment," "write up the results of...", "I ran X, help me document it," "pre-register this," "update the entry for...", or when the user shares results and asks for help interpreting and recording them. The skill enforces the four-way separation between what happened, what it means, what it implies, and what comes next; challenges the user's interpretations with evidence requests and alternative explanations; and writes incrementally to keep context clean and the entry always grounded. |
| version | 1.0.2 |
| author | Hermes Agent |
| license | MIT |
| metadata | {"hermes":{"tags":["research","experiment-log","interview","documentation"],"related_skills":["experiment-log-structure","research-proposal-structure"]}} |
Experiment Log Interview
What this skill does
Runs the human-facing interview layer for building or updating a single experiment entry.
Use experiment-log-structure as the canonical definition of the artifact itself. This interview skill is intentionally thinner: it focuses on mode detection, questioning, challenge, and incremental writing discipline rather than re-specifying the full experiment-entry schema.
The output still becomes the standard experiment log artifact, but this skill's job is to get accurate, calibrated content into that artifact through a structured Socratic process.
When to use
Trigger on requests like: "log this experiment," "write up the results of X," "help me document a backtest," "pre-register this run," "I have results, help me interpret them," "update the entry for...", or whenever the user shares experimental results in a context where they are likely to want a durable record.
Do NOT use for:
- informal scratchpad notes,
- cross-experiment retrospectives,
- direct artifact generation when the needed content is already known — use
experiment-log-structure.
Three modes — identify before interviewing
Always determine the lifecycle mode before deep questioning:
- Mode A — Pre-registration
- Mode B — Post-run write-up
- Mode C — Revision of an existing entry
If the mode is unclear, ask: "Is this a new experiment you haven't run yet, results you're writing up, or a revision to an existing entry?"
Use experiment-log-structure as the source of truth for what each mode implies for the document contract.
Core workflow
Step 1 — Mode + scaffold
After identifying the mode:
- Load the structural contract from
experiment-log-structure.
- For Modes A/B, copy
references/template.md to a working file (default: experiments/<short-slug>.md unless the user specifies another path).
- For Mode C, read the existing file in full before asking further questions.
- Tell the user the file path and the mode you are operating in.
Everything after this point edits the entry itself.
Step 2 — Interview, gated by mode
Read references/interview-guide.md once. It contains the per-section question bank and challenge protocol.
Interview discipline:
- Ask one focused question at a time.
- After each substantive answer, apply the balanced challenge protocol.
- Update the markdown immediately after each meaningful exchange.
- Quote back a short excerpt of what you wrote.
- Push once for specificity on missing numbers or comparisons; if unavailable, record a TODO tied to the source of truth.
Mode handling:
- Mode A: fill only the pre-results sections, then stop.
- Mode B: fill the post-run sections while preserving any frozen pre-registration content.
- Mode C: append a dated addendum instead of silently rewriting substantive earlier claims.
Step 3 — Exploration at key moments
Read references/exploration.md for exact prompts.
Three moments are worth the latency:
- after raw evidence is assembled: skeptical-reader pass,
- before interpretation is finalized: alternative-explanation pass,
- before decision & next step is finalized: calibration check.
Condense sub-agent output into short bullets before it enters the document. Bring the most important finding back to the user as a question.
Step 4 — Coherence and freeze
Before finishing:
- verify that interpretation is supported by evidence,
- verify that confidence is proportionate,
- verify that implications and next steps connect back to the broader proposal/question,
- verify that any frozen pre-registration content stayed frozen,
- verify that revisions preserve the audit trail.
Then present the completed file path and current lifecycle state.
Operating principles
Pre-registration remains sacred. The structure skill defines the freeze boundary; this interview skill must respect it.
Evidence is shown, not claimed. Push for the comparison behind every claim.
One question at a time. The interview is Socratic, not a survey.
Negative and null results are first-class. Document them with the same rigor.
Sub-agents return summaries, not transcripts. Keep the main thread centered on the user.
The structure lives in the companion skill. If you find yourself re-deriving the experiment-entry schema, reload experiment-log-structure and conform to it.
Reference files
references/template.md — experiment-entry scaffold copied at the start.references/interview-guide.md — interview questions and challenge prompts.references/exploration.md — sub-agent / scoped-pass prompts.
