| name | techdebt |
| description | Locate technical debt in a subsystem or architectural component of a codebase. Use when the user runs `/techdebt <subsystem>` or asks to audit a module for smells, duplication, prop drilling, dead code, or other debt patterns. Examples: "/techdebt src/auth", "find tech debt in components/docs-panel", "audit the interactive-engine for smells". |
techdebt — Locate Technical Debt in a Subsystem
Confidence-tiered audit. Disqualifiers are hard filters, not soft considerations — they are what keeps the skill useful rather than noisy.
When to Use
Triggered by /techdebt <subsystem>, by phrases like "find tech debt in X" / "audit Y for smells", as pre-refactor due diligence, or as a sub-agent from /review against a PR's changed files. Requires a concrete target — if the user gives none, ask for one; do not audit the whole repo.
Invocation
/techdebt <subsystem> # all categories, high-confidence only
/techdebt <subsystem> --category A # one category
/techdebt <subsystem> --category A,B # subset
/techdebt <subsystem> --pattern B1 # single pattern
/techdebt <subsystem> --suggestive # also emit suggestive-tier findings
Categories:
- A — Local syntactic (A1–A5). Single-file, fast.
- B — Cross-file structural / corpus similarity (B1–B4). Slowest — agent acts as similarity judge.
- C — Delegation and architectural / graph-level (C1–C4). Uses import graph + churn.
- D — Process debt (D1 Stale Memory Drift, D2 Test-Generation Debt).
- E — Operational debt / extraction seams (E1–E6). High-risk refactor targets: imperative resource managers, async state machines, singletons, module-level registries, contract-surface scatter, bootstrap orchestration. Each E finding is scoped small enough to act on in one session.
Workflow
- Resolve target → concrete file set. Accept directory, glob, or named subsystem (consult repo's
AGENTS.md / architecture docs if the term is symbolic). Print resolved file count before continuing.
- Build inventory in one pass:
- File list with LOC
- Exported symbols per file
- Per-file churn:
git log --since="90 days ago" --pretty=format:"%H" -- <file> | wc -l
- Project dependencies: read
package.json (for B3)
- Load
PATTERNS.md from this skill directory. Re-read every invocation — do not rely on memory.
- Run each pattern against the inventory:
- Category A: read each file; scan for the signature.
- Category B: agent is the similarity engine. Normalize bodies (strip imports, JSX scaffolding, comments) before comparing. Emit the explicit similarity claim in
Evidence so it can be audited.
- Category C: build a minimal import graph via
grep -rn "from ['\"]" <subsystem>. Use git log for churn (C3).
- Category D: D1 diffs
CLAUDE.md / AGENTS.md / .cursor/rules/ docs against current code; D2 reads test files and counts meaningful assertions.
- Category E: targeted grep + read. E1 looks for paired resource APIs (
setInterval/addEventListener/*Observer) with cleanup distance; E2 looks for AbortController + debounce + retry in the same function; E3 looks for export const … = new X() then traces importers; E4 looks for top-level let / new Map() / new Set() outside any function; E5 looks for repeated string literals matching CustomEvent / storage / testid / query-param patterns; E6 inspects the project's designated entry-point file(s).
- Check disqualifiers BEFORE emitting. For every candidate hit, walk the pattern's disqualifier list. If any matches → drop the candidate. If a disqualifier cannot be verified, demote to suggestive. Never emit high-confidence with an unchecked disqualifier. The
Disqualifiers checked field on each finding is the audit trail.
- Emit findings grouped by confidence tier, ordered by hotspot score (
churn_90d × pattern_severity) within each tier. Cap output at 10 high-confidence findings; if more exist, emit a trailing ## Additional candidates (truncated) line with counts per pattern ID. Prefer not-flagging when uncertain — false positives erode trust faster than missed findings.
Confidence Tiers
- High — signature matched AND all disqualifiers ruled out. Default emit.
- Suggestive — signature partially matched, OR one or more disqualifiers couldn't be verified. Emit only with
--suggestive.
Output Format
Group findings by tier (High first, then Suggestive if requested). Within each tier, order by hotspot score descending.
Per finding
### [Pattern ID] — [pattern name]
- **Confidence**: high | suggestive
- **Locations**:
- `path/to/file.ts:12-34` — `symbolName`
- `path/to/other.ts:8-29` — `otherSymbol`
- **Evidence**: One paragraph: what was observed and why it matches the signature. For B-category, include the explicit similarity claim and what convinced you.
- **Disqualifiers checked**:
- Not generated code (no `**/*.generated.*` match)
- Functions have semantically distinct names — flagged anyway because behavior is identical
- **Hotspot**: churn 12 commits/90d (top 8%) — prioritize
- **Suggested action**: One or two sentences. Concrete: "Extract X into Y", "Replace with `lodash/debounce`", "Hoist this prop to context".
Patterns with no findings
End the report with a compact line, not per-pattern sections:
## No evidence found
A1, A3, A5 · B2, B4 · C1, C4 · D1
Do not spend output explaining what wasn't found.
When nothing is found at all
No tech debt found above the confidence threshold in <subsystem>. Run with --suggestive to include lower-confidence candidates.
Example header
Resolved → <N> files, <LOC> LOC in <subsystem>
Inventory:
- <N> exported symbols
- Hottest files (90d): <file> (<commits>), …
- Deps relevant to B3: <library list from package.json>
Running A1–E6…
High-confidence findings (<N>):
<pattern ID> — <path>:<lines> (churn <N>)
…
No evidence found: A1, A3 · B2, B4 · C2, C4 · D1
Shallow-clone fallback
If git log --since="90 days ago" returns no history (shallow CI clones), set churn=1 for all files and note Hotspot scoring degraded: shallow clone, no churn signal in the output header. Findings remain valid; only the ordering loses fidelity.
