self-awareness

name	self-awareness
description	Wisp-science's actual agent tool surface and runtime boundaries. Load this when deciding which Wisp tool can perform a task, checking whether Python can reach agent or desktop capabilities, choosing between interactive analysis and persisted Runs, or answering questions about delegation, images, skills, memory, artifacts, lineage, credentials, session history, and other self-introspection capabilities.
license	Apache-2.0

Self-awareness — Wisp's actual capabilities

Use only tools advertised in the current conversation. Wisp exposes agent and desktop capabilities as explicit tools; do not assume that an SDK documented by another application also exists here. Some tools are conditional on the desktop session, project settings, execution context, or capability grants. If a tool is not advertised, treat it as unavailable.

Python and R boundary

Use python for persistent Python analysis and r for persistent R analysis. Their variables and imports persist per project and execution context. Pass a context_id such as local, ssh:<alias>, or wsl:<distro> when the work must run somewhere other than the default local context.

The Python worker initializes an ordinary namespace with common standard-library modules and any available convenience packages. It does not inject a Wisp control-plane object. Code executed with python therefore cannot directly call the agent model, spawn Agents, submit or monitor Runs, inspect Wisp credentials, or query internal project/session metadata. Leave the Python cell and call the corresponding Wisp tool instead.

Capability reference

Need	Wisp interface	Availability and boundary
Read, create, or patch project files	read, write, edit	Operate on normal filesystem paths within the granted workspace.
Find files or text	search, grep	Use before broad manual inspection.
Run a short command	shell	Use for bounded foreground commands, not as a long-running job manager.
Interactive Python or R analysis	python, r	Persistent per project and execution context; no injected control-plane SDK.
Inspect a local image	view_image	Explicit tool call for a supported local image; this is not a Python method.
Track a multi-step plan	update_plan	Update task progress when a plan materially helps.
Present the completed result	attempt_completion	Wisp's normal completion path; there is no separate structured-output submission SDK.
Audit configured workflow guidance	list_skill_catalog	Page through discovered/effective records and use its explicit counts.
Discover and load workflow guidance	search_skills, use_skill	Search by task/domain, then load the exact returned skill name.
Search confirmed project notes	search_memory	Available only when project memory is enabled. New notes are proposed after a completed turn and require confirmation in the Wisp UI; there is no direct memory-write tool.
Delegate multi-file codebase reading	explore	Read-only sub-Agent with its own context and read/grep/search access.
Delegate general bounded tasks	delegate_tasks	Desktop-only and capability-gated. Use it only when its schema is advertised; it is not callable from Python.

Choosing the right execution path

1. Use python or r for interactive analysis whose next step depends on the computed result.
2. Use run_in_context for persisted, recoverable, or long-running work. Use monitor_run when the result is needed in the current task (again after wait_interrupted; do not resubmit), or return the Run id for fire-and-forget work.
3. Use explore when codebase understanding requires more than a couple of reads. Use delegate_tasks only when desktop delegation is currently advertised and the work benefits from independent or parallel Agents.
4. Use ordinary project files for inputs and outputs. Never fabricate an artifact registry, lineage API, credential API, session database, or Python-side bridge for a capability that is not present.

For SSH-direct details, load remote-compute-ssh; its Run workflow and current limitations are the authoritative Wisp contract.