> ## Documentation Index > Fetch the complete documentation index at: https://docs.decimal.ai/llms.txt > Use this file to discover all available pages before exploring further. # Public Skills Leaderboard — ranked by performance dimension within a window > Anonymous-readable, time-windowed ranked leaderboard. Distinct from the registry browse endpoint: - Registry `/skills?sort=` is about exploration (filter + paginate) - This endpoint is about ranking (top N by performance dimension) Axes (skill_scores_redesign §7.7 — every axis is an *earned place*, the gate is stated in the UI sub-copy): - `skill_score`: SkillScore v2 DESC, full evidence only (≥2 legs) — provisional scores never chart. Rolling 30d rollup, so `window_days` does not apply to this axis. - `biggest_improvement`: latest verified SkillTestRun in the window, pass-rate delta vs the no-skill baseline. - `efficiency`: token savings ASC (most negative = cheapest); skills that INCREASED token cost are excluded. `most_turn_savings` is the legacy param for the turns-keyed variant and keeps working. - `top_rated`: SkillRaterReport mean in the window, ≥10 rated traces (matches the v2 rater-leg gate). ## OpenAPI ````yaml /openapi.json get /api/v1/registry/leaderboard openapi: 3.1.0 info: title: DecimalAI Platform description: Agent Dataset Lifecycle Platform — Backend API version: 0.1.0 servers: [] security: - BearerAuth: [] tags: - name: traces description: >- Ingest, search, and inspect agent execution traces. A trace is the atomic unit of the platform — every other feature (evaluation, compatibility scoring, dataset building) operates on traces. Each trace is auto-tagged with the manifest hash of the agent that produced it. - name: eval-scores description: >- Push, fetch, and aggregate per-trace evaluation scores. Scores carry source provenance (built-in, DeepEval, LangSmith, custom) and feed the unified decision engine, which produces a keep / repair / replay / drop verdict per trace. - name: skills description: >- Manage reusable instruction blocks (SKILL.md files) that modify agent behavior. Skills are first-class manifest components — changes to a skill appear in your regression-check impact reports. Use these endpoints to create, version, fork, and sync skills with your local SKILL.md files. - name: manifests description: >- Register and inspect manifest versions. A manifest is a snapshot of your agent's structural identity (tools, prompts, models, skills) at a point in time. The SDK registers manifests automatically; these endpoints expose the underlying records. - name: datasets description: >- Build versioned SFT/DPO training datasets from manifest-classified, eval-scored traces. Datasets are reproducible — each version locks the manifest and filter set used to build it. Export as JSONL, Parquet, or push to HuggingFace Hub. - name: replay description: >- Re-execute historical traces against a new manifest version. Replay is the deferred-future capability for behavioral verification of agent changes. The SDK creates a replay batch, your worker executes each task, then submits results back here for eval scoring. - name: registry description: >- Browse and install community skills from the public skills registry. Each registry skill carries a SkillScore — an evidence-tiered quality composite computed from real-world evals, benchmarks, and ratings across organizations. Installing creates a fork in your org — edits don't affect the public version. - name: agents description: >- List and inspect agents, plus their multi-agent topology (orchestrator → sub-agent edges discovered from traces). Agents are identified by a stable agent_name string set in your SDK init() call. - name: import description: >- Bulk-import historical traces from another observability platform or a JSONL backup. Useful for migrating from LangSmith / Braintrust / Langfuse. Duplicate trace IDs are silently skipped — re-running an import is safe. paths: /api/v1/registry/leaderboard: get: tags: - registry summary: >- Public Skills Leaderboard — ranked by performance dimension within a window description: |- Anonymous-readable, time-windowed ranked leaderboard. Distinct from the registry browse endpoint: - Registry `/skills?sort=` is about exploration (filter + paginate) - This endpoint is about ranking (top N by performance dimension) Axes (skill_scores_redesign §7.7 — every axis is an *earned place*, the gate is stated in the UI sub-copy): - `skill_score`: SkillScore v2 DESC, full evidence only (≥2 legs) — provisional scores never chart. Rolling 30d rollup, so `window_days` does not apply to this axis. - `biggest_improvement`: latest verified SkillTestRun in the window, pass-rate delta vs the no-skill baseline. - `efficiency`: token savings ASC (most negative = cheapest); skills that INCREASED token cost are excluded. `most_turn_savings` is the legacy param for the turns-keyed variant and keeps working. - `top_rated`: SkillRaterReport mean in the window, ≥10 rated traces (matches the v2 rater-leg gate). operationId: get_leaderboard_api_v1_registry_leaderboard_get parameters: - name: sort in: query required: false schema: type: string description: >- skill_score | biggest_improvement | efficiency | top_rated (legacy: most_turn_savings) default: biggest_improvement title: Sort description: >- skill_score | biggest_improvement | efficiency | top_rated (legacy: most_turn_savings) - name: window_days in: query required: false schema: type: integer maximum: 3650 minimum: 1 description: Time window (≤3650 ≈ 'all time') default: 30 title: Window Days description: Time window (≤3650 ≈ 'all time') - name: limit in: query required: false schema: type: integer maximum: 100 minimum: 1 default: 20 title: Limit responses: '200': description: Successful Response content: application/json: schema: {} '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' components: schemas: HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError securitySchemes: BearerAuth: type: http scheme: bearer description: Enter your API key (e.g. dai_sk_test_key_001) ````