q792602257/agentic-mobile-control
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat(skill-catalog-subscription): synced catalog + HTTP sync + MCP tools

Browse Source 
Consumes the external Subscription Platform as source of truth for skill
content; reuses skills_learning domain models (extended with KnowledgeSkill)
and workflow.skill_exec resolver. HTTP/MCP deps land in api/ per
CONSTITUTION.md; synced skills use a physically separate SQLite file
(tasks/skills.sqlite3) to preserve the skill-authoring capability boundary.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
q792602257
2026-07-07 10:33:23 +08:00
co-authored by Claude Opus 4.6
parent 763c1b2299
commit b94abde92a
13 changed files with 2608 additions and 38 deletions
Download Patch File Download Diff File Expand all files Collapse all files
openspec/changes/skill-catalog-subscription/design.md
+36 -4
View File
@@ -46,6 +46,26 @@ Even though sync only ever pulls "entitled" skills, `skills/catalog.py`'s query
`skills/mcp_tools.py` exposes `get_skill` (returns metadata + content/template) and a parameter-resolution helper; it does **not** expose a `run_skill` tool that silently executes on the LLM's behalf. The LLM fetches the flow template, fills placeholders itself (or asks the user for missing required parameters), and then issues the already-existing device-capability tool calls (`tap`, `input_text`, etc.) from `apex-agent-mvp` in the order/values the template specifies.
- **Alternative considered**: Add a single `run_skill_flow(skill_id, params)` MCP tool that executes the whole sequence server-side. Rejected for this change — it would bypass the Agent Runtime's Observe→Think→Act loop and Executor retry/wait logic from `apex-agent-mvp`, silently skipping Scene verification between steps. Keeping execution inside the existing loop (LLM issues each tool call itself, informed by the template) preserves the "AI decides based on what it currently observes" principle the whole platform is built on. A batched execution helper can be revisited later as a design decision in its own change if needed.
### D6: Reuse `skills_learning/` domain models and `workflow/skill_exec.py` resolver; do not duplicate them
The archived `skill-learning-runtime` change already shipped `skills_learning/models.py` defining `SkillKind` (`"knowledge" | "flow_template"`), `SkillMetadata`, `FlowStep`, `Skill`, and `FlowTemplateSkill`, plus `workflow/skill_exec.py` with `validate_skill_args` / `resolve_skill_steps` / `_resolve_value`. This change **does not introduce a parallel `skills/` package**. Instead:
- Reuse all existing domain types verbatim. The only model-layer addition is a `KnowledgeSkill(Skill)` class in `skills_learning/models.py` (the `kind` Literal already includes `"knowledge"` but no concrete class exists for it yet).
- The MCP parameter-resolution helper (§4.2 of tasks) wraps `workflow.skill_exec.resolve_skill_steps` rather than reimplementing it.
- The archived `skill-authoring` spec (now in `openspec/specs/skill-authoring/spec.md`) explicitly anticipated this change: locally-synthesized skills live in `skills_learning/store.py` tagged `source = "local-synthesis"` and **must not write into** the externally-synced catalog store. This change honors that boundary by using a **physically separate** SQLite file (`tasks/skills.sqlite3`) for synced skills.
- **Alternative considered**: Move all shared skill domain types into `core/skill_models.py` to make the cross-feature reuse explicit. Deferred — would be a larger refactor of already-tested code, and the boundary is data-model-only (no store/runtime coupling). Revisited if a third consumer appears.
### D7: CONSTITUTION.md compliance — code lands in `core`-extended, `storage`, and `api` layers only
Per `docs/CONSTITUTION.md` lines 33-34 ("HTTP and MCP dependencies enter at `api`. No LLM, HTTP, or MCP dependency may appear in `core`, `driver`, `device`, or `tools`."), and the dependency direction `core → driver/device → tools → perception → storage → runtime → api`, this change's files map as follows:
| Concern | File (new or extended) | Layer | Allowed deps |
|---|---|---|---|
| Domain models (extend) | `skills_learning/models.py` | core (feature-scoped) | dataclasses, `core.models` only — zero HTTP/MCP/LLM |
| Synced-skill local store + query | `storage/skill_catalog.py` (new) | storage | `sqlite3`, `skills_learning.models` — zero HTTP/MCP/LLM |
| Subscription HTTP client + poll loop + webhook | `api/skill_sync.py` (new) | api | `httpx`, `storage.skill_catalog` |
| Skill MCP tools (list/search/get/resolve) | `api/skill_catalog_mcp.py` (new) | api | `mcp.server.fastmcp`, `storage.skill_catalog`, `workflow.skill_exec` |
| MCP server wire-up | `api/mcp.py` (one-line addition) | api | calls `register_skill_catalog_tools(...)` at end of `create_mcp_server` |
`core`, `driver`, `device`, `tools` receive **zero new imports** from this change. The `tasks/skills.sqlite3` file is physically separate from both `tasks/tasks.sqlite3` (task metadata) and the in-memory `skills_learning.SkillStore` (local synthesis), preserving the archived `skill-authoring` spec's "no cross-writes" contract at the storage layer.
## Risks / Trade-offs
- **[Risk]** The Subscription Platform's actual API shape is unknown/assumed (`fetch_entitled_skills`, optional webhook) → **Mitigation**: keep `skills/sync_client.py` behind a small internal interface (similar to `Driver` in `apex-agent-mvp`) so the concrete HTTP client can be adjusted once the real Subscription Platform API is finalized, without touching `catalog.py` or `mcp_tools.py`.
@@ -53,13 +73,25 @@ Even though sync only ever pulls "entitled" skills, `skills/catalog.py`'s query
- **[Risk]** Flow-template skills reference tools/parameters that drift from the actual `tools/` function signatures in `apex-agent-mvp` (e.g. a template calls a tool that was renamed) → **Mitigation**: validate a flow template's `tool` names against the currently registered MCP/tool set at sync time (or at least at `get_skill` time) and surface a clear "skill unavailable/invalid" error rather than letting a bad call reach the device.
- **[Trade-off]** No local skill authoring/editing keeps this change simple and avoids ownership ambiguity, but means Apex Agent is fully dependent on the Subscription Platform being reachable at least once to have any skills at all — acceptable since the platform is a required dependency by design, not an optional enhancement.
- **[Trade-off]** Not providing a server-side `run_skill_flow` execution tool keeps flow templates consistent with the Observe-Think-Act loop, at the cost of the LLM needing a few more tool-call round trips per flow skill than a single batched call would take — acceptable given the platform's core principle of always re-observing between actions.
- **[Risk]** Reusing `skills_learning/models.py` as the domain model for synced skills couples this change to the `skills_learning` feature package. If either consumer (local synthesis or external sync) needs a divergent model shape, ripple effects result. → **Mitigation**: the coupling is at the data-model layer only — no store, runtime, or executor coupling exists. If a third consumer appears or divergence is needed, refactor the shared types into `core/skill_models.py` as a separate cleanup change (not blocking this one).
## Migration Plan
Additive only: new `skills/` package, new MCP tools, and new local storage tables/files. No existing `apex-agent-mvp` code paths are modified (only composed with, per D-decisions above). If `apex-agent-mvp` has already been applied, this change's MCP tools register onto its existing MCP server instance; if not yet applied, `skills/mcp_tools.py` can stand up its own MCP server instance for independent testing and be merged once `apex-agent-mvp` lands. Rollback is simply removing the `skills/` package and its MCP tool registrations; no data migration or schema changes to existing tables are required.
Additive across existing packages — no new top-level package is introduced:
- **`skills_learning/models.py`**: gains one new dataclass (`KnowledgeSkill`). No changes to existing types; existing tests in `tests/test_skill_*.py` are unaffected.
- **`storage/skill_catalog.py`** (new): independent module + a new SQLite file `tasks/skills.sqlite3`. Does not touch `storage/task_metadata.py`'s `tasks/tasks.sqlite3` or `skills_learning/store.py`'s in-memory store.
- **`api/skill_sync.py`** (new): HTTP sync client + poll runner + webhook handler. Self-contained; the webhook registers on the existing FastAPI app from `apex-agent-mvp` if applied, or stands alone for testing.
- **`api/skill_catalog_mcp.py`** (new): MCP tool registration helper.
- **`api/mcp.py`**: one-line addition — `register_skill_catalog_tools(server, ...)` called at the end of `create_mcp_server`. Existing device-capability tools are unchanged.
- Rollback: remove the four new/extended files and delete `tasks/skills.sqlite3`. No data migration or schema changes to existing tables are required.
If `apex-agent-mvp` is not yet applied, `api/skill_catalog_mcp.py` can stand up its own MCP server instance for independent testing (mirroring the original migration note); otherwise it composes onto the existing server via the one-line wire-up above.
## Open Questions
- Exact Subscription Platform API contract (auth mechanism, request/response shapes, whether it supports `since_version` incremental sync or only full-catalog fetch) — to be confirmed with that platform's team/spec before `skills/sync_client.py` is finalized; this design assumes an interface shape that can absorb either.
- Whether flow-template `args_template` placeholders need a richer expression language (e.g. simple conditionals) or plain `{param}` substitution is sufficient for the MVP — left open, default to plain substitution and revisit if a real skill needs more.
- Where the local Skill Catalog lives relative to `apex-agent-mvp`'s existing SQLite task-metadata DB (same DB file, new tables, vs. a separate DB/file) — deferred to implementation time in `tasks.md`, doesn't affect the capability contracts defined here.
- Exact Subscription Platform API contract (auth mechanism, request/response shapes, whether it supports `since_version` incremental sync or only full-catalog fetch) — to be confirmed with that platform's team/spec before the concrete `HttpSubscriptionClient` in `api/skill_sync.py` is finalized. The `SubscriptionClient` Protocol (§3.1 of tasks) is shaped to absorb either full or incremental fetch; the concrete HTTP mapping is the only thing that changes once the real API is known.
- Whether flow-template `args_template` placeholders need a richer expression language (e.g. simple conditionals) or plain `{param}` substitution is sufficient for the MVP — left open, default to plain substitution (matching existing `workflow.skill_exec._resolve_value`) and revisit if a real skill needs more.
## Resolved Questions
- **Local catalog storage location** (previously open): resolved by D7 — a physically separate SQLite file at `tasks/skills.sqlite3`, owned by `storage/skill_catalog.py`. Chosen to preserve the archived `skill-authoring` spec's "no cross-writes between local-synthesis and synced-skill stores" contract at the storage layer (separate files make the boundary physical, not just conventional). Reusing `tasks/tasks.sqlite3`'s file with new tables was rejected because it would couple sync-skill schema migrations to task-metadata migrations.