executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
zooFoolbox model-zoo guidance for loading local or remote Foolbox-compatible repositories, implementing foolbox_model.py create() contracts, fetching weights, and diagnosing networked model-loader failures.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this route when a task mentions foolbox.zoo, get_model,
foolbox_model.py, ModelLoader, shared model repositories, downloaded model
weights, or a GitCloneError. Read references/api-reference.md
for signatures and references/workflows.md for
local and remote procedures.
The checker command in the workflow reference is relative to the generated Foolbox skill root, not a native Foolbox checkout and not the caller's current directory. From any cwd, set the root and change into it first:
# Replace this non-executable placeholder with the absolute directory containing the root SKILL.md.
export SKILL_ROOT=/path/to/installed/skills/disco/foolbox
cd "$SKILL_ROOT"
Use the actual skill-root path when it differs from this installation, or use an
absolute script path. Local checker output is temporary and does not write model
zoo data into the skill. get_model() clones into Foolbox's cache and
fetch_weights() writes downloads/extractions there (typically under
~/.foolbox_zoo), not beside these documents; record and inspect the returned
path before cleanup. Plot or report files belong in an explicit absolute output
directory such as "$SKILL_ROOT/outputs/", never in source/reference assets.
The local checker is offline. A zoo clone or weights download/extraction is
networked and may execute untrusted code or consume substantial disk; obtain
explicit approval immediately before zoo.get_model(...) or
zoo.fetch_weights(...), even if a cache entry exists. Do not treat cache
presence as approval.
foolbox_model.py, and validate create() without network.
Run scripts/check_local_zoo_model.py.fb.zoo.get_model(url, module_name='foolbox_model', overwrite=False, **kwargs) clones into Foolbox's cache and imports the module.
This executes remote code and may install/use framework dependencies; obtain
approval before cloning.fb.zoo.fetch_weights(uri, unzip=False) downloads to a
Foolbox cache; unzip=True extracts ZIP or tar.gz archives. Treat this as a
networked, potentially large operation and verify checksums/provenance outside
the normal smoke path.A compatible model module must expose create(**kwargs) and return a Foolbox
Model wrapper. The default module name is foolbox_model. Keep model loading
separate from attack benchmarking so a failed clone or weight download does
not look like an attack failure.
Use references/troubleshooting.md for module
imports, invalid URLs, missing create(), return types, cache/overwrite,
network failures, and archive extraction. Do not run remote examples from the
original repository as part of a routine offline verification.