phantom-quench
SolidInput-tracing grounding audit for artifacts such as test cases, analysis reports, and design docs. Extracts proper nouns, numbers, citations, version claims, and branching conditions, then back-traces each to declared local files by grep or to external sources by fetch-and-support checks. Marks missing anchors as Phantom Claims and cited-but-unsupporting anchors as Unsupported. A claim is grounded only by non-model evidence: a local hit or literal source span, never another model's agreement. Renamed from source-grounding-audit; old-name references still route here. Triggered by: "phantom detection", "phantom claim", "source back-trace", "where did this come from", "verify source", "does the source support this claim", "grounding audit", "source grounding audit", "citation support check".
Install
Quality Score: 83/100
Skill Content
Details
- Author
- chrono-meta
- Repository
- chrono-meta/forge-harness
- Created
- 3 months ago
- Last Updated
- today
- Language
- Shell
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
steel-quench
All-angle verification meta-skill for near-complete artifacts. Turns vague design anxiety into structured challenger waves using fh-commons:quench-challenger, then drives defense and convergence until root weaknesses, residual risks, and added complexity are explicit. Covers standard attack/defense rounds, optional Meta-Aware Adversary mode for AI-specific risks such as hallucination, context collapse, prompt injection, and tool lock-in, and Wave-P3 re-attack after an upstream gate declares PASS. Built-in outputs emphasize attack-plus-prescription pairs and can feed fh-meta:persona-innovator after convergence. Triggered by: "quench this", "devil's judgment", "all-angle review", "end-to-end verification", "steel quench", "deep pre-completion inspection", "did it really pass?".
goal-quench
Wraps /goal with a tiered safety + orchestration ladder. core (default): a token budget gate (pre-run estimate), mid-run budget thresholds, and an automatic post-run quality verification via pipeline-conductor — closing /goal's two gaps (the runner's per-turn judge evaluates completion, pipeline-conductor evaluates correctness). pro: adds context-doctor token reduction and agent-composer goal decomposition. max: adds internal-first capability-gap fill (LOCAL_SKILL_REGISTRY skill-bus scan → plugin-recommender external search → auto_project_mapping map/cluster) and cross-ecosystem-synergy-detection pre-validation. The Phase-1 budget verdict auto-recommends the mode. Triggered by "goal with quality gate", "safe goal", "goal-quench", "orchestrate this goal", or before running /goal on high-stakes tasks.
deep-grounding
Invoke when you are about to assert a checkable claim or start a non-trivial analysis, design, diagnosis, or recommendation and need to ground it against the real sources before committing. Ask "where could the evidence for this be?", read the relevant sources, follow their leads recursively, and report conclusions with evidence tiers plus any residual unknowns. Use this **PROACTIVELY** when you catch yourself answering from memory, from a single source or angle, or when a result beats your expectation and could skip verification.