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# Contributing: new knowledge entry
## What you're adding
A structured YAML file containing GPU specs, performance heuristics, counter
catalogs, or other reference data. Knowledge is the immutable reference layer
that tools and agents consult without executing LLM calls.
## File locations
- Data: `perfxpert/knowledge/<name>.yaml`
- JSON schema: `perfxpert/knowledge/_schemas/<name>.schema.json`
- Tests: `tests/test_knowledge/test_<name>.py`
## Template
### YAML skeleton
```yaml
# perfxpert/knowledge/<name>.yaml
version: "1.0"
metadata:
description: "One-sentence description"
maintained_by: "your-handle or team"
last_updated: "2026-04-18"
entries:
- id: entry_1
field: "value"
- id: entry_2
field: "value"
```
### JSON schema skeleton
```json
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"version": {"type": "string"},
"metadata": {
"type": "object",
"properties": {
"description": {"type": "string"},
"maintained_by": {"type": "string"},
"last_updated": {"type": "string"}
},
"required": ["description"]
},
"entries": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {"type": "string"},
"field": {"type": "string"}
},
"required": ["id"]
}
}
},
"required": ["entries"]
}
```
## Schema constraints (CI-enforced)
- Every YAML has a corresponding `.schema.json` in `_schemas/`
- `test_yaml_schemas.py` validates all YAML files against their schemas on every PR
- Schema follows JSON Schema draft-07
- YAML load must pass pyyaml (no circular refs, no code injection)
## Tests you must add
- `test_<name>_loads_without_error()` — happy path
- `test_<name>_validates_against_schema()` — schema conformance
- `test_<name>_has_required_fields()` — spot-check key entries
- `test_<name>_ids_are_unique()` — no duplicate IDs if applicable
## Review requirements
- 1 core reviewer
- CI green (schema + load validation)
## Conventions for advanced entries
### `applies_to_gfx` — arch gating
Knowledge entries that only apply to a subset of GPU architectures
MUST carry an `applies_to_gfx` list — the consuming agent fences
(`compute_specialist`, `memory_specialist`, …) gate the entry
behind a membership check against the active `gfx_id`. Pattern:
```yaml
entries:
- id: mfma_matrix_meter
applies_to_gfx: ["gfx908", "gfx90a", "gfx942", "gfx950"]
# ...
```
`matrix_meter.yaml` + `attention_patterns.yaml` are the canonical
examples; `proven_optimizations.yaml` + `compiler_pragmas.yaml` use
the same field for selective entries. Entries that apply universally
omit the field. The fence slice that reads the entry MUST include
`applies_to_gfx` in its allowlist so the gate can narrow at runtime.
### `units` on `expected_impact` — numeric semantics
Knowledge entries that quote a numeric `expected_impact` MUST pair
it with a `units` field so downstream rendering knows how to
interpret the value. Canonical values in the current tree:
- `time_saved_fraction` — e.g. `0.25` = 25% less wall time.
- `speedup_multiplier` — e.g. `1.35` = 1.35× faster.
- `bandwidth_fraction_of_peak` — for memory-bound recommendations.
`fusion_patterns.yaml` threads `units: time_saved_fraction` through
every `expected_impact` entry; the same convention is expected of
any new YAML that emits an impact estimate.
## Common pitfalls
- Schema must be a valid JSON Schema draft-07 (not hand-wavy)
- YAML IDs used by tools/agents for lookup — keep them stable
- If you edit an existing YAML, schema might also need to change (version bump + backcompat note)
- Comments in YAML are allowed; comments in JSON schemas are not
## Related docs
- Existing knowledge under `perfxpert/knowledge/` as references
- JSON Schema handbook: https://json-schema.org/
- test_yaml_schemas.py for validation patterns