Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/agent-sh/agentsys/drift-analysisnpx skills add agent-sh/agentsys --skill drift-analysisgit clone --depth 1 https://github.com/agent-sh/agentsysWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.01960 |
| Opus 5 | $0.00023 | $0.00980 |
| Sonnet 5 | $0.00009 | $0.00392 |
| Haiku 4.5 | $0.00005 | $0.00196 |
Grade A, and why
drift-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drift Analysis
Knowledge and patterns for analyzing project state, detecting plan drift, and creating prioritized reconstruction plans.
Architecture Overview
/drift-detect
│
├─→ collectors.js (pure JavaScript)
│ ├─ scanGitHubState()
│ ├─ analyzeDocumentation()
│ └─ scanCodebase()
│
└─→ plan-synthesizer (Opus)
└─ Deep semantic analysis with full context
Data collection: Pure JavaScript (no LLM overhead) Semantic analysis: Single Opus call with complete context
Drift Detection Patterns
Types of Drift
Plan Drift: When documented plans diverge from actual implementation
- PLAN.md items remain unchecked for extended periods
- Roadmap milestones slip without updates
- Sprint/phase goals not reflected in code changes
Documentation Drift: When documentation falls behind implementation
- New features exist without corresponding docs
- README describes features that don't exist
- API docs don't match actual endpoints
Issue Drift: When issue tracking diverges from reality
- Stale issues that no longer apply
- Completed work without closed issues
- High-priority items neglected
Scope Drift: When project scope expands beyond original plans
- More features documented than can be delivered
- Continuous addition without completion
- Ever-growing backlog with no pruning
Detection Signals
HIGH-CONFIDENCE DRIFT INDICATORS:
- Milestone 30+ days overdue with open issues
- PLAN.md < 30% completion after 90 days
- 5+ high-priority issues stale > 60 days
- README features not found in codebase
MEDIUM-CONFIDENCE INDICATORS:
- Documentation files unchanged for 180+ days
- Draft PRs open > 30 days
- Issue themes don't match code activity
- Large gap between documented and implemented features
LOW-CONFIDENCE INDICATORS:
- Many TODOs in codebase
- Stale dependencies
- Old git branches not merged
Prioritization Framework
Priority Calculation
function calculatePriority(item, weights) {
let score = 0;
// Severity base score
const severityScores = {
critical: 15,
high: 10,
medium: 5,
low: 2
};
score += severityScores[item.severity] || 5;
// Category multiplier
const categoryWeights = {
security: 2.0, // Security issues get 2x
bugs: 1.5, // Bugs get 1.5x
infrastructure: 1.3,
features: 1.0,
documentation: 0.8
};
score *= categoryWeights[item.category] || 1.0;
// Recency boost
if (item.createdRecently) score *= 1.2;
// Stale penalty (old items slightly deprioritized)
if (item.daysStale > 180) score *= 0.9;
return Math.round(score);
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 325 lines · 45 tokens per session scan A 86d7c61064db
drift-analysis is a skill published in the GitHub repository agent-sh/agentsys (980 stars, last pushed 5d ago), licensed MIT. It adds 45 tokens to every session and 1,960 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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