script-first

name	script-first
description	Collapses deterministic multi-step repository research, aggregation, indexing, validation, and transformation into one small purpose-built local script and one Bash run. Use when a task would otherwise require 6+ related read/search/tool calls, iterates over many files or records, cross-references results, or requests batch analysis; do not use for small exploration or broad mutations.

Script-first

For deterministic multi-step work, prefer one purpose-built script in one Bash run over a model -> tool -> model chain.

Use when

• 6+ related read/search calls are likely.
• Iterating over files, records, URLs, or command output.
• Aggregating, indexing, validating, extracting, or cross-referencing known data.
• The desired result and output shape are clear before execution.

Examples: TODO inventory, symbol index, test/config coverage report, cross-file consistency check, batch metadata extraction.

Do not use when

• A single file or grep -> read -> done is enough.
• The next action materially depends on interpreting an unknown result.
• The work makes broad, irreversible, external, or user-visible changes.
• A human decision or confirmation is required between steps.

Do not manufacture a script merely to satisfy this skill.

Procedure

1. State the narrow question and bounded input scope.
2. Write one small script, usually Python with stdlib plus subprocess for local CLI tools.
3. In that script: discover inputs, read/process them, aggregate, and print only the requested result.
4. Run it through one Bash invocation. Prefer a quoted heredoc or mktemp script under /tmp; do not leave artifacts unless they are useful deliverables.
5. Handle expected per-input failures and report compact partial results.
6. Inspect the result. Run a second script only if the first result exposes a real new question.

Boundaries

• Default to read-only. Keep writes explicit, narrowly scoped, and separately justified.
• Do not use the script to bypass Pi guardrails, path policy, confirmation, or secret restrictions.
• Do not read credentials, auth files, .env files, or unrelated home directories.
• Do not download or execute remote code.
• Keep output under roughly 5 KB: counts, summaries, selected findings, and truncation notices. Never dump full file contents or unfiltered large lists.
• Use deterministic ordering and include paths/line numbers where useful.

Good shape

python3 - <<'PY'
from pathlib import Path

hits = []
for path in sorted(Path("src").rglob("*.py")):
    try:
        for number, line in enumerate(path.read_text(errors="replace").splitlines(), 1):
            if "TODO" in line:
                hits.append(f"{path}:{number}: {line.strip()}")
    except OSError as error:
        print(f"WARN {path}: {error}")

print(f"TODOs: {len(hits)}")
print("\n".join(hits[:100]))
if len(hits) > 100:
    print(f"... truncated {len(hits) - 100} more")
PY

One Bash call. Script performs discovery, processing, and reduction. Model interprets compact result afterward.