plugins/utils/skills/execution-mode/SKILL.md
Set or report the reproducibility mode governing how AIWG workflows execute, from standard to fully auditable
npx skillsauth add jmagly/aiwg execution-modeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You set or report the reproducibility mode that governs how AIWG workflows execute, controlling determinism constraints from none (standard) to fully auditable (audit).
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
| Pattern | Example | Action |
|---------|---------|--------|
| Set standard | "use default execution mode" | Run aiwg execution-mode standard |
| Set seeded | "use a fixed seed for this run" | Run aiwg execution-mode seeded --seed <value> |
| Set strict | "make execution deterministic" | Run aiwg execution-mode strict --seed <value> |
| Set audit | "enable audit mode" | Run aiwg execution-mode audit --seed <value> |
| Status check | "what execution mode is active?" | Run aiwg execution-mode (no args) |
| Seed only | "set seed to 42" | Run aiwg execution-mode seeded --seed 42 |
When triggered:
Extract intent:
standard, seeded, strict, or audit?--seed value provided or should one be generated?Run the appropriate command:
# Report current mode (no args)
aiwg execution-mode
# Standard — no reproducibility constraints
aiwg execution-mode standard
# Seeded — fixed random seed for all operations
aiwg execution-mode seeded --seed 42
# Strict — seeded + no external calls + pinned versions
aiwg execution-mode strict --seed 42
# Audit — strict + decision logging for replay
aiwg execution-mode audit --seed 42
Mode summary:
| Mode | Seed | External calls | Pinned versions | Decision log |
|------|------|----------------|-----------------|--------------|
| standard | No | Allowed | No | No |
| seeded | Yes | Allowed | No | No |
| strict | Yes | Blocked | Yes | No |
| audit | Yes | Blocked | Yes | Yes |
Persistence: Mode is written to .aiwg/execution-mode.json and persists across sessions until explicitly changed.
Report the result — confirm the mode that is now active and note any implications (e.g., external calls will be blocked in strict/audit mode).
User: "What execution mode are we in?"
Extraction: Status check, no change requested
Action:
aiwg execution-mode
Response: "Current execution mode: seeded (seed: 1234). External calls are allowed and versions are not pinned. To increase determinism, switch to strict or audit mode."
User: "Make the workflow fully deterministic with seed 42"
Extraction: Strict mode requested, seed 42 provided
Action:
aiwg execution-mode strict --seed 42
Response: "Execution mode set to strict with seed 42. External network calls are blocked and dependency versions are pinned. Mode saved to .aiwg/execution-mode.json."
User: "Enable audit mode so we can replay every decision"
Extraction: Audit mode requested, no seed provided — generate one
Action:
aiwg execution-mode audit --seed 7391
Response: "Execution mode set to audit with seed 7391. All decisions will be logged for replay. Seed chosen automatically — note it if you need to reproduce this run exactly."
User: "Reset execution mode back to default"
Extraction: Reset to standard mode
Action:
aiwg execution-mode standard
Response: "Execution mode reset to standard. No reproducibility constraints are active."
If the user's intent is ambiguous:
seeded (fixed seed only), strict (seed + pinned versions + no external calls), or audit (strict + decision logging)?"data-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.