Auditing Part11 Trails

What it does

When your agent uses it

• The user runs OpenMed in a regulated/validated environment and needs an attributable
• Tamper-evident record of each processing action
• Electronic-signature manifestations
• Computer-system-validation (CSV) evidence

Example prompts

• “Use the auditing-part11-trails skill to generate and verifies 21 CFR Part 11-style audit trails — who/what/when, electronic signatures, and…”
• “/auditing-part11-trails”

Requirements

• Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Authenticate the actor in your own IdP/access system (Part 11 needs unique
2. 2Run the processing step with audit=True to get the deterministic record.
3. 3Sign with a controlled release key from a vault/HSM; record key_id.
4. 4Build the Part 11 envelope — who, when (UTC, contemporaneous), what, and
5. 5Append, never overwrite. Store trails write-once (WORM / append-only
6. 6Verify on retrieval with .verify(key, original_text=..., deidentified_text=...)
7. 7Retain per the study/retention schedule; keep keys and any reversible

What it can do on your machine

Read from SKILL.md and the folder at commit 34d7b8c. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • fda.gov
  • ecfr.gov
  • ispe.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Auditing Part11 Trails loads about 2.2k tokens when it runs. Until then it costs about 232 tokens; SKILL.md has 727 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~232

When it runs · the whole SKILL.md, loaded when a task matches

~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from maziyarpanahi/openmed at commit 34d7b8c, republished under its Apache-2.0 licence (© maziyarpanahi). 727 words, ~2,222 tokens.

name

auditing-part11-trails

description

Generates and verifies 21 CFR Part 11-style audit trails — who/what/when, electronic signatures, and tamper-evidence — for OpenMed pipelines in GxP and clinical-trial (GCP) settings. Use when the user runs OpenMed in a regulated/validated environment and needs an attributable, time-stamped, tamper-evident record of each processing action, electronic-signature manifestations, or computer-system-validation (CSV) evidence. Trigger keywords: 21 CFR Part 11, Part 11, audit trail, electronic signature, e-signature, GxP, GCP, GLP, GMP, CSV, computer system validation, data integrity, ALCOA, tamper-evident, contemporaneous. Pairs adjacent to OpenMed: maps directly onto OpenMed deidentify(audit=True) -> signed AuditReport with .sign(key)/.verify(key), whose repro_hash + HMAC give the tamper-evidence and attribution Part 11 expects. This is a compliance-enablement aid, not a validation certification.

license

Apache-2.0

metadata.project

OpenMed

metadata.category

compliance-regulatory

metadata.pairs

adjacent

metadata.version

1.0

import openmed, json, datetime as dt

note = "Subject S-014 (DOB 1962-08-09) reported headache on 2024-05-01."

# 1) Produce the deterministic, PHI-free audit record for this processing step.
report = openmed.deidentify(note, policy="hipaa_safe_harbor", audit=True)

# 2) Sign it with a controlled release key (stored in a vault / HSM, never in code).
report.sign(b"<release-hmac-key>", key_id="omv-signer-2026")

# 3) Wrap in a Part 11 envelope: who / when / what / signature meaning.
trail = {
    "record": report.to_dict(),              # tamper-evident, no PHI
    "who": "j.smith@sponsor.example",        # authenticated user (your IdP)
    "when": dt.datetime.now(dt.timezone.utc).isoformat(),
    "what": "PHI de-identification of source narrative (study X, subject S-014)",
    "signature_manifestation": {             # 21 CFR 11.50
        "signer_printed_name": "Jane Smith",
        "meaning": "reviewed and approved",
        "signed_at": dt.datetime.now(dt.timezone.utc).isoformat(),
    },
    "system": {"openmed_version": report.openmed_version,
               "manifest_hash": report.manifest_hash},
}
with open("part11_trail.json", "w") as fh:
    json.dump(trail, fh, indent=2, sort_keys=True)

# 4) Later — verify integrity (optionally bind to the exact source/output text).
ok = report.verify(b"<release-hmac-key>", original_text=note)
assert ok, "AUDIT TRAIL TAMPERED OR KEY MISMATCH"

© maziyarpanahi, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/auditing-part11-trails of maziyarpanahi/openmed.

Open the folder on GitHubat commit 34d7b8c