intent-drift

name	intent-drift
description	Detects intent drift in AI-assisted development by comparing the original goal against the current plan and execution context. Run /intent-drift to evaluate whether ongoing work has drifted from what was asked. Triggers on "check intent drift", "are we still on track", "is this aligned with the goal", "did the plan drift", "intent alignment", "scope creep check", "am I off track".

intent-drift

A skill that uses the Intent Alignment Engine to detect whether an AI coding agent's current work has drifted from the user's original goal.

Run (when invoked)

0. Gather inputs (ask only what you cannot infer from the repo):

• --original-goal (required): the user's stated objective, or infer from the conversation / issue / PR description if available.
• --current-plan (required): what is actually being built right now (steps, branch purpose, recent edits), or infer from git state + recent messages.
• --context / --auto-context: execution evidence (edited files, git diff, recent commands). With --auto-context, collect automatically (see scripts/collect_context.py). Auto-context is repo-only by default: git diff, commits, edited files, and file changes. Your shell history is never read unless you pass --include-shell-history. That opt-in is deliberate — .bash_history / .zsh_history can contain credentials typed into a shell and commands unrelated to the current repo, so it stays off unless explicitly requested. Auto-collected context is also scrubbed by default: secret-like content (tokens, password=/api_key= assignments, Authorization: headers, long base64 blobs) is masked before it reaches the analyzer and report exporters. To disable the scrub (not recommended), construct ContextCollector(sanitize_secrets=False).
• --format (text | markdown | json): output format.
• --threshold (default 75): minimum alignment % to be considered "on track".

Do NOT ask if enough is inferable from the repo + conversation — infer and state your assumptions.

1. Build the context and call the analyzer:

python3 ~/.claude/skills/intent-drift/analyzer.py \
  --original-goal "Reduce memory usage" \
  --current-plan "Optimize startup latency" \
  --context "Edited: main.py, startup.py. Recent: pip install numpy, cProfile main.py" \
  --format text

Or in Python:

sys.path.insert(0, str(Path.home() / ".claude" / "skills" / "intent-drift"))
from analyzer import IntentDriftAnalyzer
a = IntentDriftAnalyzer()
rep = a.analyze(a.parse_arguments([
    "--original-goal", "Reduce memory usage",
    "--current-plan", "Optimize startup latency",
]))
print(a.export_report(rep, "text"))

2. Report to the user:

• Overall alignment %, status (Fully_Aligned → Critical_Drift), and confidence %.
• The recommendation verbatim.
• The 2–3 strongest evidence lines (✅ / ⚠ / ❌) with their source provider.
• If alignment < threshold: highlight the drifted dimension from the breakdown.

3. If drift is detected, surface it clearly and suggest pausing to confirm intent before continuing — do not silently keep building the off-track plan.

How it works

Nine evidence providers each inspect the same context and emit weighted Evidence (value 0–100, confidence 0–1). The engine computes a weighted score, a consistency-based confidence, a status band, and a recommendation. Providers live in providers/, exporters in exporters/, and auto context collection in scripts/collect_context.py.

Provider	Weight	What it checks
goal_provider	0.25	Semantic overlap between goal and plan
constraint_provider	0.20	Constraints satisfied / violated
scope_provider	0.15	Scope expansion or reduction
execution_provider	0.15	Commands / edits / reasoning vs goal
file_graph_provider	0.10	File relationships and patterns
dependency_provider	0.10	Dependency install/remove vs goal
architecture_provider	0.10	Architectural change patterns
requirement_coverage_provider	0.08	Success criteria coverage
problematic_findings_provider	0.07	Cross-provider problematic patterns

Rules

• State assumptions when inferring goal/plan from the repo; never fabricate intent.
• Below-threshold results are a call to confirm, not a reason to abandon good work.
• Prefer --auto-context so evidence reflects real repo state, not just prose.
• This skill is a maintainer tool, not a replacement: it pauses and asks for confirmation — it never acts autonomously or re-plans the work itself.

Files

File	Purpose
analyzer.py	CLI + IntentDriftAnalyzer (parse → analyze → export)
providers/	9 evidence providers + base.py
exporters/	text / markdown / json report exporters
scripts/collect_context.py	Repo-only context collection (git diff, commits, edited files, file changes) with default-on secret scrubbing; shell history is opt-in via --include-shell-history
config/defaults.yaml	Thresholds, weights, enabled providers
metadata.json	Importable skill metadata (params, deps)