Pack the right inputs

For diagnose a confusing dashboard screenshot using image evidence plus written context, assemble only what changes the answer: cropped screenshot, task goal, UI version, visible labels, expected behavior, sensitive-area redactions, and requested evidence format. Label each item by authority and date. A source-of-truth document outranks a memory-based note; a current error log outranks a description of last month's behavior. State conflicts instead of letting the model blend them.

Use a four-part packet: task, evidence, constraints, and output contract. Put untrusted content inside clear delimiters and say that it is data, not instruction. Include representative examples, especially one normal case and one boundary case. Omit irrelevant history; excess context can hide the one line that controls the result.

Inspect this redacted checkout dashboard screenshot. Goal: explain why the conversion total appears inconsistent. First inventory only visible labels and values with locations. Separate observation from inference. Then propose three hypotheses and the next screenshot or log needed to test each. Do not identify people, infer hidden fields, or invent unreadable text.

Before sending, annotate the packet. Mark which values are verified, which are illustrative, and which are unknown. If a screenshot is involved, transcribe critical small text. If structured data is involved, include headers, units, software version, and null behavior. If creative material is involved, record ownership and permitted use. This is how context becomes operational rather than decorative.

A useful response would look like this: An observation table grounded in screen regions, clearly labeled hypotheses, and targeted follow-up evidence instead of a confident visual guess. That description is intentionally observable. “Looks good” is not acceptance. The operator must zoom and compare source pixels, transcribe critical values manually, reproduce in the product, inspect logs, and reject claims unsupported by visible or supplied evidence. Keep the source material beside the draft so review means comparison, not memory.

The privacy boundary is specific: crop and redact names, faces, addresses, notifications, account IDs, location clues, EXIF metadata, and confidential browser tabs before upload. Create the smallest synthetic example that preserves the problem. Replace names and identifiers consistently so relationships remain testable. Redaction is not merely drawing a box: crop surrounding notifications, remove metadata where relevant, and check that hidden sheets, comments, or revision history are not included.

Poor packets lead to predictable failures: hallucinated small text; mixing observation with inference; ignoring chart scale; accidental exposure around the crop; treating an image as current truth. Another common failure is silently changing the source packet mid-run. Save a version or hash of the inputs beside the output, especially when another person will reproduce the work.

Rate a packet from zero to two on six dimensions: relevance, authority, recency, completeness, privacy, and reproducibility. A score below two on authority or privacy blocks the run. A low completeness score does not invite invention; it creates a question for the owner.