DemonGatanjieuandClaude Opus 5.5
0764683c52
Antigravity, Claude Code, Cursor and VS Code load tool descriptions on demand themselves; looking tools up through Anomalous (tool_help, use_tool) only doubled that: in one Gemini 3.8 Flash run 18 of 29 calls went to it, while full-set chats had none. tool_help, use_tool, action_catalog.DAILY, ai_gates.tool_set and the Gates row go. An app still holding an older list is now told apart by the list it fetched last (a fingerprint per app in anomalous/ai_tool_lists.json), so the note under the task header also covers an Anomalous update. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
109 lines
5.5 KiB
Python
109 lines
5.5 KiB
Python
"""What each thing an AI app can do through Anomalous's MCP endpoint is, in one place.
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Every tool (mcp_tools.py reads, mcp_actions.py acts, mcp_task_tools.py the AI's own) has an
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entry here: its kind (the AI workbench's colour, words and counts; None = not a step of its
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own), the stage of the work it belongs to (the flow over a task: models, combo, prompt,
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canvas, run, pictures, voice, library) and its gate (what it touches or costs, for the user's
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rules on what needs their OK: canvas, gpu, download, network, files; None = nothing to guard).
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tests/test_ai_tasks.py keeps this catalog and the tools in step.
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The user's own changes in Anomalous (activity log actions) get stages too, so the ones made
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while an AI works sit in the same flow as its steps (ai_tasks.note_activity).
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"""
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from collections import namedtuple
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Entry = namedtuple("Entry", "kind stage gate")
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STAGES = ("model", "combo", "prompt", "canvas", "run", "picture", "voice", "library")
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GATES = ("canvas", "gpu", "download", "network", "files")
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# Arguments with which a call also changes the canvas: it then asks as the stricter of its own gate and "canvas".
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ALSO_CANVAS = {"run_workflow": ("workflow", "prompt", "negative", "seed", "width", "height", "image", "image_node", "values")}
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TOOLS = {
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# reading
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"library_overview": Entry("look", "library", None),
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"search_models": Entry("look", "model", None),
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"get_model": Entry("look", "model", None),
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"scan_report": Entry("look", "library", None),
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"search_images": Entry("look", "picture", None),
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"get_image_info": Entry("look", "picture", None),
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"zoom_image": Entry("look", "picture", None),
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"list_combos": Entry("look", "combo", None),
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"list_workflows": Entry("look", "canvas", None),
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"list_saved_prompts": Entry("look", "prompt", None),
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"search_audio": Entry("look", "voice", None),
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"recent_activity": Entry("look", "library", None),
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"describe_canvas": Entry("look", "canvas", None),
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"get_situation": Entry("look", None, None), # the task, the canvas in brief and the next step (mcp_situation.py)
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"check_workflow_models": Entry("look", "model", None),
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"download_status": Entry("look", "model", None),
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"list_voices": Entry("look", "voice", None),
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# acting
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"set_prompt": Entry("canvas", "prompt", "canvas"),
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"set_model": Entry("canvas", "model", "canvas"),
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"add_lora": Entry("canvas", "model", "canvas"),
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"place_combo": Entry("canvas", "combo", "canvas"),
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"fix_workflow_models": Entry("canvas", "model", "canvas"),
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"find_nodes": Entry("look", "canvas", None),
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"add_node": Entry("canvas", "canvas", "canvas"),
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"add_nodes": Entry("canvas", "canvas", "canvas"),
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"connect_nodes": Entry("canvas", "canvas", "canvas"),
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"set_values": Entry("canvas", "canvas", "canvas"),
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"remove_nodes": Entry("canvas", "canvas", "canvas"),
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"new_workflow": Entry("canvas", "canvas", "canvas"),
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"open_workflow": Entry("canvas", "canvas", "canvas"),
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"run_workflow": Entry("run", "run", "gpu"),
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"download_missing_models": Entry("download", "model", "download"),
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"download_model": Entry("download", "model", "download"),
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"move_model": Entry("act", "model", "files"),
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"scan_models": Entry("scan", "library", "network"),
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"speak": Entry("speech", "voice", "gpu"),
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"open_in_anomalous": Entry("show", "model", None),
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# the AI's own: notes and panels are steps; the rest only steer the task
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"report": Entry("note", None, None),
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"log_decision": Entry("decision", None, None),
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"log_outside": Entry("outside", None, None), # what it did with other tools (ai_outside.py, which also notes what changed)
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"show_panel": Entry("panel", None, None),
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"ask_user": Entry("panel", None, None),
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"propose_repaint_area": Entry("panel", "picture", None),
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"show_run_map": Entry("panel", None, None),
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"begin_task": Entry(None, None, None),
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"track_run": Entry(None, "run", None), # attaches an existing submission; creates its own run step
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"update_panel": Entry(None, None, None),
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"get_answers": Entry(None, None, None),
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"run_status": Entry("look", "run", None),
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"stop_run": Entry(None, "run", None), # ends a run step of its own; the step says who stopped it
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"get_toolbox": Entry(None, None, None),
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# Anomalous's card in the conversation (mcp_apps.py): its own calls, not the AI's steps
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"app_task_view": Entry(None, None, None),
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"app_answer": Entry(None, None, None),
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}
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# Activity log actions (activity_log.py ROUTE_ACTIONS, and "canvas") the user makes in Anomalous
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# that belong in the task an AI is working on, with their stage. Downloads, imports, moves, scans
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# and backups are left out: an AI's own calls can cause those too.
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USER_ACTIONS = {
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"canvas": "canvas",
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"model_edit": "library", "model_cover": "library", "model_delete": "library",
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"recipe_save": "canvas", "recipe_edit": "canvas", "recipe_delete": "canvas", "recipe_restore": "canvas",
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"material_save": "prompt", "material_edit": "prompt", "material_delete": "prompt",
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"preset_save": "run", "preset_rename": "run", "preset_delete": "run",
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"image_delete": "picture", "audio_delete": "voice", "audio_save": "voice", "voice_settings": "voice",
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"note_save": "library", "note_delete": "library",
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}
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def entry(tool, read_only=True):
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"""The catalog entry of `tool`; one not listed is a read, or an act when it is not read-only."""
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found = TOOLS.get(tool)
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if found:
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return found
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return Entry("look" if read_only else "act", None, None)
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def is_step(tool):
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"""Whether a call of `tool` is a step of its own in a task."""
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return entry(tool).kind is not None
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