agent-spectrum
# Agent Spectrum
Use this directory as the canonical `Agent Spectrum` skill package.
## Canonical Files
- `references/scoring-spec.md`
- `references/output-template.md`
- `references/localization-dictionary.md`
- `examples/quick-full.zh.md`
- `examples/quick-full.en.md`
- `examples/quick-partial.zh.md`
- `examples/quick-partial.en.md`
- `examples/deep-full.zh.md`
- `examples/deep-full.en.md`
Do not rely on repo-root wrappers as the source of truth. Those wrappers should route here.
## Execution Order
1. Load `references/scoring-spec.md`, `references/output-template.md`, and `references/localization-dictionary.md`.
2. Default the assessment target to the current agent unless the user explicitly asks to score another agent.
3. Resolve `output_language` before rendering:
- explicit user language instruction wins
- this package currently supports only `zh-CN` and `en`
- explicit `en` requests must render in `en`
- explicit `zh` / `zh-CN` requests must render in `zh-CN`
- explicit unsupported locales that belong to the Sinosphere or historically Chinese-writing sphere, such as `ja` and `ko`, must map to `zh-CN`
- otherwise, if the latest user request is mainly written in Chinese, Japanese, Korean, or another clearly Sinosphere / historically Chinese-writing language, default to `zh-CN`
- otherwise, if the latest user request is mainly written in English, use `en`
- otherwise default to `en`
4. Score observable inputs first.
5. Resolve ownership for every unanswered field:
- `operator_provided` for setup-level inputs a human holder can answer
- `self_assessed` for deep self-assessment inputs that only the target agent should answer
6. If the target is the current agent, complete deep self-assessment fields inside the agent rather than asking the human user to answer them.
7. If the target is a third-party agent and deep self-assessment inputs cannot be obtained from that target, do not produce `deep-full`; downgrade to `quick-partial` or stop at quick mode.
8. Always render `Hexagon Block` and `Coordinate Card Block` before `Evidence` and `Totals`.
9. Render the result using the exact locale family in `references/output-template.md`.
10. Check the example that matches both the result mode and `output_language` if formatting, ownership, or field semantics are ambiguous.
## Output Contract
- Always emit the required fixed fields from the selected locale family in `references/output-template.md`.
- Always include `version`, `mode`, `is_partial`, `evidence`, `totals`, `type`, `faction`, `weakest_axes`, and `tie_break`.
- For partial results, explicitly list `missing_inputs`.
- For deep results, explicitly state whether the deep result overrides the quick result.
- Always include both required visual blocks even in `quick-partial`.
- `quick-full` must include the locale-matched bridge CTA section after `说明 / Notes`, covering both community partner-finding and the next move into Deep Edition.
- `deep-full` must include the locale-matched community partner-finding CTA section after `进化建议 / Guidance`.
- `quick-partial` must not include community CTA blocks.
- Keep the full visible output monolingual after `output_language` is chosen.
## Guardrails
- Keep the original six-axis scoring system unless the user explicitly asks to redesign the framework.
- Treat `Q4-Q12` and `behavior_traces` as self-assessment inputs by default. Do not redirect them to a human user unless the user is explicitly operating as the target agent's proxy and the spec allows that field to be operator-provided.
- Normalize `GPT-5 / GPT-5.x / Codex` into `R+15, A+15`.
- Cap `X` at `35` for type judgment while preserving raw `X` in totals.
- Treat type pairs as unordered pairs. `R+A` and `A+R` are the same pair.
- Treat `weakest_axes` as a list, not a single scalar.
- Do not mix Chinese field labels with English evidence labels, faction names, tier names, or visual-block labels in the same rendered result.
- `M/R/G/A/S/X`, host names, model names, tool brands, URLs, filesystem paths, and agent names may remain as-is.
The long-form documents at repo root are optional human-readable references, not execution specs.
标签
skill
ai