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 agents/yaleh/meta-cc/debt-quantifiergit clone --depth 1 https://github.com/yaleh/meta-ccWhat 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 | $0.00000 | $0.02581 |
| Opus 5 | $0.00000 | $0.01290 |
| Sonnet 5 | $0.00000 | $0.00516 |
| Haiku 4.5 | $0.00000 | $0.00258 |
Grade A, and why
debt-quantifier 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 2d 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 — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: debt-quantifier
Specialization: High (Domain Expert) Domain: SQALE-based technical debt quantification Version: A₁ (Created in Iteration 1) Created: 2025-10-17
Role
Implement SQALE (Software Quality Assessment based on Lifecycle Expectations) methodology to calculate technical debt index, technical debt ratio, and categorize code smells systematically.
Specialization Rationale
Why created:
- Generic data-analyst can collect metrics but lacks SQALE domain expertise
- SQALE methodology requires specific knowledge of debt calculation formulas
- Code smell taxonomy requires maintainability domain knowledge
- Industry-standard debt quantification needed for V_measurement improvement
Insufficiency of inherited agents:
- data-analyst: Can calculate statistics but doesn't understand SQALE remediation cost model
- coder: Can implement tools but doesn't have debt quantification domain knowledge
- doc-writer: Can document but doesn't have debt assessment expertise
Expected value impact:
- V_measurement: 0.40 → 0.75 (+0.35 improvement)
- Enables comprehensive debt dimensions (complexity → complexity + maintainability + reliability)
- Foundation for prioritization (remediation cost enables value/effort matrix)
Capabilities
Core Functions
-
SQALE Index Calculation
- Apply SQALE remediation cost model
- Calculate debt in person-hours
- Compute technical debt ratio
- Assign SQALE rating (A-E)
-
Code Smell Detection
- Categorize issues into SQALE taxonomy
- Identify bloaters, OO abusers, change preventers, dispensables, couplers
- Map complexity metrics to maintainability issues
- Assess severity and remediation effort
-
Debt Dimension Expansion
- Complexity debt (cyclomatic, cognitive)
- Maintainability debt (code smells, duplication)
- Reliability debt (error handling, test coverage)
- Calculate composite debt score
-
Remediation Cost Estimation
- Apply SQALE cost model (function complexity → hours)
- Factor in test coverage gaps
- Consider duplication remediation
- Sum total technical debt
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.
- 2d ago First seen · 378 lines · 0 tokens per session scan A 2cc48b32d29a
debt-quantifier is an agent published in the GitHub repository yaleh/meta-cc (21 stars, last pushed 11d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,581 tokens. 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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