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DemonGatanjieu-Anomalous_Mo…/api/action_catalog.py
T
DemonGatanjieuandClaude Opus 5.5 68342ad61d Give an AI where things stand in one call, and what is still unwired
A small model lost its way wiring the canvas: describe_canvas says what
feeds each input but not what is still free or what fits it, so it
looked up every node type and kept the graph in mind, and long answers
were filed away by Antigravity for the AI to open.

get_situation (mcp_situation.py) gives the task (what the user asked
last, what waits for them, decisions, pictures, steps outside AMB), the
canvas in brief (mcp_canvas_brief.js: a line per node, the inputs a run
needs that nothing feeds yet with the outputs that fit, ComfyUI's
errors), the latest run and the next step, kept under 3,600 characters.
add_node, connect_nodes and remove_nodes answer with what is still
unwired. The connect sentence, the rules and the instructions point a
new chat to get_situation first.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-24 03:37:49 +08:00

104 lines
5.2 KiB
Python

"""What each thing an AI app can do through Anomalous's MCP endpoint is, in one place.
Every tool (mcp_tools.py reads, mcp_actions.py acts, mcp_task_tools.py the AI's own) has an
entry here: its kind (the AI workbench's colour, words and counts; None = not a step of its
own), the stage of the work it belongs to (the flow over a task: models, combo, prompt,
canvas, run, pictures, voice, library) and its gate (what it touches or costs, for the user's
rules on what needs their OK: canvas, gpu, download, network, files; None = nothing to guard).
tests/test_action_catalog.py keeps this catalog and the tools in step.
The user's own changes in Anomalous (activity log actions) get stages too, so the ones made
while an AI works sit in the same flow as its steps (ai_tasks.note_activity).
"""
from collections import namedtuple
Entry = namedtuple("Entry", "kind stage gate")
STAGES = ("model", "combo", "prompt", "canvas", "run", "picture", "voice", "library")
GATES = ("canvas", "gpu", "download", "network", "files")
TOOLS = {
# reading
"library_overview": Entry("look", "library", None),
"search_models": Entry("look", "model", None),
"get_model": Entry("look", "model", None),
"scan_report": Entry("look", "library", None),
"search_images": Entry("look", "picture", None),
"get_image_info": Entry("look", "picture", None),
"zoom_image": Entry("look", "picture", None),
"list_combos": Entry("look", "combo", None),
"list_workflows": Entry("look", "canvas", None),
"list_saved_prompts": Entry("look", "prompt", None),
"search_audio": Entry("look", "voice", None),
"recent_activity": Entry("look", "library", None),
"describe_canvas": Entry("look", "canvas", None),
"get_situation": Entry("look", None, None), # the task, the canvas in brief and the next step (mcp_situation.py)
"check_workflow_models": Entry("look", "model", None),
"download_status": Entry("look", "model", None),
"list_voices": Entry("look", "voice", None),
# acting
"set_prompt": Entry("canvas", "prompt", "canvas"),
"set_model": Entry("canvas", "model", "canvas"),
"add_lora": Entry("canvas", "model", "canvas"),
"place_combo": Entry("canvas", "combo", "canvas"),
"fix_workflow_models": Entry("canvas", "model", "canvas"),
"find_nodes": Entry("look", "canvas", None),
"add_node": Entry("canvas", "canvas", "canvas"),
"connect_nodes": Entry("canvas", "canvas", "canvas"),
"set_values": Entry("canvas", "canvas", "canvas"),
"remove_nodes": Entry("canvas", "canvas", "canvas"),
"new_workflow": Entry("canvas", "canvas", "canvas"),
"open_workflow": Entry("canvas", "canvas", "canvas"),
"run_workflow": Entry("run", "run", "gpu"),
"download_missing_models": Entry("download", "model", "download"),
"download_model": Entry("download", "model", "download"),
"move_model": Entry("act", "model", "files"),
"scan_models": Entry("scan", "library", "network"),
"speak": Entry("speech", "voice", "gpu"),
"open_in_anomalous": Entry("show", "model", None),
# the AI's own: notes and panels are steps; the rest only steer the task
"report": Entry("note", None, None),
"log_decision": Entry("decision", None, None),
"log_outside": Entry("outside", None, None), # what it did with other tools (ai_outside.py, which also notes what changed)
"show_panel": Entry("panel", None, None),
"ask_user": Entry("panel", None, None),
"show_run_map": Entry("panel", None, None),
"begin_task": Entry(None, None, None),
"track_run": Entry(None, "run", None), # attaches an existing submission; creates its own run step
"update_panel": Entry(None, None, None),
"get_answers": Entry(None, None, None),
"run_status": Entry("look", "run", None),
"stop_run": Entry(None, "run", None), # ends a run step of its own; the step says who stopped it
"get_toolbox": Entry(None, None, None),
# Anomalous's card in the conversation (mcp_apps.py): its own calls, not the AI's steps
"app_task_view": Entry(None, None, None),
"app_answer": Entry(None, None, None),
}
# Activity log actions (activity_log.py ROUTE_ACTIONS, and "canvas") the user makes in Anomalous
# that belong in the task an AI is working on, with their stage. Downloads, imports, moves, scans
# and backups are left out: an AI's own calls can cause those too.
USER_ACTIONS = {
"canvas": "canvas",
"model_edit": "library", "model_cover": "library", "model_delete": "library",
"recipe_save": "canvas", "recipe_edit": "canvas", "recipe_delete": "canvas", "recipe_restore": "canvas",
"material_save": "prompt", "material_edit": "prompt", "material_delete": "prompt",
"preset_save": "run", "preset_rename": "run", "preset_delete": "run",
"image_delete": "picture", "audio_delete": "voice", "audio_save": "voice", "voice_settings": "voice",
"note_save": "library", "note_delete": "library",
}
def entry(tool, read_only=True):
"""The catalog entry of `tool`; one not listed is a read, or an act when it is not read-only."""
found = TOOLS.get(tool)
if found:
return found
return Entry("look" if read_only else "act", None, None)
def is_step(tool):
"""Whether a call of `tool` is a step of its own in a task."""
return entry(tool).kind is not None