GPT

Gather Evidence

Step 2 - Gather evidence 1. Orient first. Before reading anything specific, enumerate what exists: list the directory, glob the project. You cannot pick the right files to read from memory of what projects usually con

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## Step 2 - Gather evidence

1. Orient first. Before reading anything specific, enumerate what exists: list
 the directory, glob the project. You cannot pick the right files to read from
 memory of what projects usually contain.
2. Primary sources beat memory. Read the actual code, files, and output. Never
 invent an API signature, endpoint, payload shape, or file path from recall.
 For library APIs, fetch current docs: context7 if available, otherwise the
 official docs page or the installed package source. If neither is possible,
 say explicitly that you are working from memory.
3. Parallelize what is independent and expensive. Web fetches, doc lookups,
 subagent explorations, and reads across many files go in one parallel batch.
4. Read narrow, never re-read. Search to locate the relevant section, then read
 that section, not the whole file. Never re-fetch what is already in context.
5. Time-box mechanically. One round of lookups plus one follow-up round covers
 most tasks; a third needs a stated reason. If two consecutive lookups told you
 nothing new, stop.
6. Establish intent before changing behavior. A failing check has two possible
 culprits: the code or the check itself. Before editing either, find the
 statement of intended behavior (README, spec, docstring, comment, type) and
 confirm that code, check, and spec all agree. If any two disagree, surface the
 contradiction, say which side you trust and why, and never silently make one
 side match another. The task framing can itself be wrong.
7. Surprises route the loop. Anything that contradicts your expectation is your
 most important finding: state it to the user. If it changes what done means,
 update Step 1. If it changes what the user is actually asking for, go back to
 Step 0. Otherwise report it and continue.

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