This repository does not publish universal token, latency, quality-zone, throughput, or efficiency guarantees. Those values depend on the exact revision, selected files, tokenizer, model, agent runtime, tool behavior, context policy, project evidence, and cache state.
| Measure | Definition | Required report fields |
|---|---|---|
| Bytes | Raw UTF-8 byte count of each loaded file | commit/tag, path, byte count |
| Lines | Physical line count using one stated tool | commit/tag, path, tool/version, line count |
| Tokens | Tokens produced by a named tokenizer over exact file bytes | commit/tag, paths, tokenizer/model/version, per-file and total counts |
| Load set | Exact skill and supporting files supplied to an agent for one stage | profile, paths, inclusion order, full vs selected sections |
| Runtime | Wall-clock duration for a defined scenario | hardware, runtime/model, cache state, repetitions, raw samples |
| Outcome | Pass/fail against a versioned evaluation suite | suite revision, policy thresholds, results, failures, waivers |
File size is not model quality, execution speed, or task cost. A sections_index is navigation metadata; it does not prove that a host loads only selected sections. Referencing an artifact by path defers content loading but does not make project-scale context cost constant.
- Check out a clean, identified commit or tag and record
git rev-parse HEAD. - Declare the profile and exact paths under measurement. Include supporting files such as C-Suite primitives if the runtime loads them.
- Hash each input file and preserve the ordered path list.
- Measure bytes and lines with stated tool versions.
- For token counts, use the production model's documented tokenizer when available. Record tokenizer package, version, encoding, normalization, and special-token settings. If unavailable, label any estimate as an estimate and state the formula.
- For runtime or quality comparisons, define a fixed task corpus, hardware/runtime, model parameters, tool permissions, cache state, and policy. Run enough repetitions to report raw samples plus median and spread.
- Store commands, environment metadata, raw output, exclusions, and date with the report so another person can repeat it.
Example inventory commands on macOS/Linux:
git rev-parse HEAD
wc -c -l agile-v-core/SKILL.md requirement-architect/SKILL.md logic-gatekeeper/SKILL.md
shasum -a 256 agile-v-core/SKILL.md requirement-architect/SKILL.md logic-gatekeeper/SKILL.mdTokenizer commands are intentionally not prescribed because this repository has no tokenizer dependency and model tokenization differs. Do not use a generic bytes-to-tokens ratio as measured data.
- Compare identical task corpora and evidence obligations; do not compare a compact skill to an unspecified body of “equivalent documentation.”
- Separate prompt/input tokens, generated/output tokens, tool-return tokens, and persisted artifacts where the runtime exposes them.
- Report cold and warm cache runs separately.
- Treat parallel execution as a scheduling strategy, not an automatic speedup; dependencies, contention, edits, and rate limits can reduce or reverse gains.
- Publish negative and failed runs. Do not infer “zero information loss,” “peak quality,” or scalability from file compression alone.
- Re-run measurements after skill, profile, runtime, model, tokenizer, or evaluation-suite changes.
Load only the stage-relevant profile from Installation Profiles, pass durable evidence by path, and use fresh independent contexts where the lifecycle requires independence. These are context-management practices, not quantified performance claims.