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Generate committed example inputs by profiling real workloads: workload scripts, generation, inspection, and validation. Use when asked to add an input or example for a language, profiler, or configuration.
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Based on SOC occupation classification
Implement a new origin end-to-end. Use when asked to add or support a new origin, or when a new profiler tool or runtime starts emitting inputs. One origin per emitting tool or runtime, always, even when its inputs carry no detectable markers.
Implement a new profile format end-to-end: research, input generation, converter, origin decision, registration, tests, docs, and examples. Use when asked to support, add, or implement a new format.
Implement a new modality end-to-end: aggregated form, modality module, converter union, pipeline dispatch, options, tests, and docs. Use when asked to add a modality, or when a format fits neither supported modality.
Generate a performance profile, identify hotspots, and optimize.
Profile a benchmark, identify hotspots, and optimize.
| name | new-input |
| description | Generate committed example inputs by profiling real workloads: workload scripts, generation, inspection, and validation. Use when asked to add an input or example for a language, profiler, or configuration. |
| argument-hint | [language, origin, format, or guidance] |
| allowed-tools | Bash(pnpm generate-inputs *) |
Generate committed example inputs in examples/input/ by profiling real
workloads.
$ARGUMENTS
If loaded from /new-format, skip step 1 and return to that workflow after step
3: the remaining steps assume the converter already exists.
src/formats/registry.ts: STOP, load
/new-format, and follow its workflow instead; it implements the format
end-to-end and returns here to generate inputssrc/origins/specs/index.ts: load /new-origin
and follow its workflow first; input filenames carry the origin's
registered ID, and every committed input must resolve to itAdd or update workload scripts in scripts/inputs/, one per emitting
language (<lang>.sh, sharing the _common.sh helpers), then run
pnpm generate-inputs <langs>:
docker_capture; host tools may need
additions to scripts/inputs/flake.nix<lang>.<origin>.<config?>.<base|current>.<ext>; the second
token must be the origin's registered ID, and the extension must match the
converter's extensionverify_generated_input
fails oversized captures). An oversized input means the workload does too
much work while recording (high-volume configs like nativemem record
every event): shrink the workload's input or iteration count, not the
profiler flags, so the capture stays realisticInspect the generated bytes by hand: confirm each file is the intended format, the workload's own code dominates the samples, and the origin's evidence (marker entries or a parser origin hint) is present
Convert each input with node src/cli/index.ts <input>, and each
base/current pair as a diff. Sanity-check the output against the workload
Run the detected-input-origins test (pnpm test src/origins/index.test.ts):
every committed input must resolve to the origin in its filename. NEVER
commit an input that resolves elsewhere: give the origin a marker or a parser
origin hint, or make the workload realistic enough to carry the origin's
evidence
For a language we don't list yet: add a languageMetas entry (name, aliases,
extensions) in src/cli/languages.ts and generation instructions in
docs/languages/<language>.md, then verify the docs render with
node src/cli/index.ts --help <language>. If a new config token needs a
display label beyond title-casing, add it to configNames in
src/cli/examples.ts
pnpm update-examples, then pnpm update-readme