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“Write inline documentation and a README for a previously undocumented internal Python module”
Summary · Write inline docstrings for all functions, classes, and methods in a previously undocumented internal Python module (assumed ~500–1500 lines), plus a README covering purpose, installation, usage examples, and API overview.
Documenting existing code from source is one of AI's strongest use cases: the code is the ground truth, the task is generative and structured, and errors are caught in review by comparing doc against code. AI eliminates the slow read-then-draft cycle and produces consistent style automatically. Human review is still required to catch logic mischaracterizations but is much faster than writing from scratch.
Where AI helps most
AI eliminates the slow read-comprehend-draft loop for every function — generating a full first draft of all docstrings and the README in minutes rather than hours, leaving the human only the verification step.
10× / week
10.5 hrs
saved per week using AI
Worker comparison
six profiles| Worker | Time | Cost | Quality & caveats | Conf. |
|---|---|---|---|---|
|
01
Solo Individual
First-timer, no specialist knowledge
|
4–8 hours | $0 out-of-pocket (own time); ~$20–40 in tools if any | Will likely be incomplete or inconsistent — missed parameters, vague descriptions, no docstring style convention followed. README may lack useful examples. Significant risk of mischaracterizing edge-case behavior without deep code understanding. | medium |
|
02
Solo Expert
Skilled professional in this field
|
1–3 hours | $100–300 at ~$100–120/hr | Will choose an appropriate docstring style (Google, NumPy, or reST), cover parameters, return types, and exceptions accurately. README will be clear and practical. Quality scales with familiarity with the codebase — highest if they wrote the module. | high |
|
03
Small Team
2–3 people, mixed skills
|
2–4 hours elapsed | $400–900 (2–3 people at mixed $80–150/hr rates) | Splitting code author (accuracy) and technical writer (clarity) yields strong results. Coordination overhead adds some elapsed time. Peer review improves consistency and catches omissions the author would overlook. | high |
|
04
Agency
Professional service provider
|
4–8 hours billable | $800–2,000 at $150–250/hr blended agency rate | High polish and consistent style. Significant time spent on onboarding and context-building since they don't own the code. Will often produce a documentation standard template that can be reused. Overkill for a single small module but appropriate for a shared library. | medium |
|
05
Enterprise
Large org, process & overhead
|
2–5 days elapsed (3–6 hours active work) | $1,200–3,500 fully loaded (developer time + review cycles + tooling) | Process overhead dominates: ticketing, style-guide compliance review, manager sign-off, CI doc-lint checks. Output is thorough and audit-ready but delivery is slow. Quality is high if the code author is involved; lower if delegated to a separate doc team without adequate handoff. | medium |
|
AI
AI (Claude / Agent)
AI plus competent human review
|
30–75 minutes total (5–15 min AI generation + 25–60 min human review) | $2–10 in API credits + ~$50–80 human reviewer time | AI (e.g. Claude) is genuinely strong here: given the source code it produces well-structured docstrings, infers parameter types, and drafts a README skeleton quickly. Main failure modes: may mischaracterize subtle logic, hallucinate edge-case behavior, or miss side effects not visible from signatures. Human reviewer must read the module and verify factual accuracy — skipping review risks shipping plausible but wrong docs. Overall output quality is good to excellent after review. | high |
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