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SKILL verified MIT Self-run

Bug Fix

skill-techygarg-lattice-bug-fix · by techygarg

Investigate, reproduce, and safely fix a bug with regression protection. Composes context, diagnosis, architecture, code quality, and testing guardrails into a reproduce-first repair workflow. Use when the user says 'fix this bug', 'debug this', 'investigate this failure', 'patch this regression', 'repair this issue', or 'why is this broken'.

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Install

$ agentstack add skill-techygarg-lattice-bug-fix

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Bug Fix

Required Skills

Load these skills based on bug scope (see Steps 2 and 5 for when):

  1. framework:knowledge-priming -- (always)
  2. framework:context-anchoring -- (always)
  3. framework:learning-harvest -- (always)
  4. framework:collaborative-judgment -- (always)
  5. framework:clean-code -- (always)
  6. framework:test-quality -- (always)
  7. framework:architecture -- (conditional)
  8. framework:domain-driven-design -- (conditional)
  9. framework:secure-coding -- (conditional)

Workflow

Step 1: Establish Bug Context

Start from failure, not proposed fix.

  • Gather observed behavior, expected behavior, reproduction path, any evidence: failing test, error message, stack trace, log excerpt, request payload, recent change.
  • Use framework:learning-harvest Load behavior. Focus hint: "bug investigation — focus: reliability, quality signals".
  • Use framework:context-anchoring Document Discovery to check for existing context doc for affected feature/module.
  • If found → Load it (context-anchoring Load behavior). Honor logged decisions + constraints as active commitments while diagnosing.
  • If not found → Proceed from bug report + current code. Don't block diagnosis on missing context.

End this step, summarize bug one sentence:

> "Observed X, expected Y, reproducible via Z."

STOP: If can't state bug clearly yet, gather more evidence before proposing code changes.

Step 2: Reproduce and Localize

Primary discipline: don't present fix for bug you haven't reproduced.

Reproduce failure using strongest evidence available, this order:

  1. Existing failing automated test -- best case; use as regression guard
  2. New failing automated test -- preferred when no test exists yet
  3. Executable reproduction path -- command, request sequence, deterministic manual flow when automation not yet possible

Localize issue before editing:

  • Which layer likely source? Use layer definitions from framework:architecture to identify which architectural layer defect originates in
  • Production bug or test bug? Sometimes code correct, test/fixture wrong
  • Failure symptom or root cause? Crashing line often downstream of real defect
  • Bug cross trust boundary? If yes, plan load framework:secure-coding
  • Involve domain invariants or aggregate behavior? If yes, plan load framework:domain-driven-design
  • Likely fix touch multiple layers or dependency flow? If yes, plan load framework:architecture

If multiple plausible root causes remain, use framework:collaborative-judgment to present leading hypotheses + what evidence would distinguish.

Before writing regression test, state root cause hypothesis explicitly, use framework:collaborative-judgment to surface:

> "Bug caused by [X]. When [C holds], correct outcome should be [P]. > Confirm this by writing test that red before fix, green after."

If user identifies flaw in hypothesis, revise before writing tests.

End step with explicit bug contract:

> C (bug condition): [exact input/state triggering bug] > P (fix postcondition): [what correct behavior looks like when C holds] > Preserved: [what must remain identical for all inputs outside C]

STOP: If can't state all three, keep localizing before writing tests.

Optional persistence check: Now that bug reproduced + localized, decide whether persist investigation:

  • If investigation complex, involves multiple hypotheses, likely span multiple sessions, ask if user wants persist diagnosis + repair decisions
  • If relevant context doc exists → plan enrich in Step 7
  • If none exists + user wants persistence → propose creating one, confirm doc name per framework:context-anchoring, use as source of truth
  • If user doesn't want persistence or bug narrow + local → continue non-persistent mode. Repair workflow still applies; decisions remain in-session

Step 3: Add Regression Protection First

Phase A — Bug-Condition Tests (must start RED)

  • Write smallest failing test that fires when C holds
  • Prefer lowest-level test reproducing real failure without losing signal
  • Name test for broken behavior, not implementation detail
  • Assert correct expected outcome (postcondition P), not just absence of failure
  • Apply framework:test-quality inline
  • Run against unfixed code, confirm RED
  • If green before fix, bug condition hypothesis wrong — stop, re-localize

Stopping rule:

  • STOP: If can't create stable failing automated test, explain why before making code changes.
  • Record closest executable reproduction you have.
  • Don't present speculative fix as "complete" without automated reproducer unless user explicitly accepts limitation.
  • If bug can't be tested directly due to tight coupling/deep integration, introduce minimum structural seam needed to make testable (method extraction, parameter injection, interface boundary). Not refactor — prerequisite for regression protection. Apply framework:clean-code inline, keep seam minimal.

Phase B — Preservation Baseline (must stay GREEN)

  • Identify existing tests covering behavior outside C
  • If important adjacent behavior has no test coverage, add at most 2-3 targeted characterization tests
  • Confirm all preservation baseline tests green before applying fix
  • These tests must remain green through every change in Step 5 — any flip to red means fix has side effects; stop, narrow scope

Step 4: Choose the Minimal Safe Fix

Separate repair strategy from code change itself.

Before editing, decide:

  • What root cause?
  • What smallest safe change correcting it?
  • What layer right repair location?
  • Does issue require local patch or small structural correction?

Default to smallest safe fix restoring correct behavior without architectural backsliding.

Guardrails:

  • Apply framework:architecture layering rules when choosing repair location — don't patch in outer layer when rule belongs inward
  • Don't widen task into unrelated cleanup
  • Don't delete/weaken failing test just to make suite green
  • If real fix requires contract/design change beyond narrow repair, stop, discuss scope explicitly
  • Don't add guard clauses, null checks, defensive handling for inputs outside C — code path for correct inputs must be byte-for-byte identical before + after fix.

If multiple valid repair strategies with meaningful trade-offs, present using framework:collaborative-judgment before proceeding.

Step 5: Implement the Fix

Always apply:

  • framework:clean-code -- keep delta focused, readable, easy to reason about
  • framework:test-quality -- maintain regression test + any nearby supporting tests

Conditionally apply based on localized root cause:

  • If fix changes layer responsibilities, dependency direction, architectural flow → Apply framework:architecture
  • If fix changes domain behavior, invariants, aggregate boundaries, value objects → Apply framework:domain-driven-design
  • If fix touches input validation, authorization, queries, external boundaries, sensitive data → Apply framework:secure-coding

After implementing fix, before presenting:

  1. Re-run regression test, confirm now green
  2. Run applicable atom self-validation checklists against changed code
  3. Run applicable anti-pattern scans
  4. Fix any violations before presenting result

Step 6: Verify Non-Regression

Verify repair three levels:

  1. Fix proof -- regression test that was red before fix now green. Asserts correct outcome, not just absence of original failure.
  2. Preservation proof -- tests covering behavior adjacent to bug still pass. If preservation baseline tests added in Step 3, must remain green. Any flip from green to red means fix has side effects — stop, narrow scope before continuing.
  3. Structural confidence -- fix didn't introduce wrong-layer workaround, dependency violation, weakened security posture

When reporting completion, explicit about verification scope:

  • What was re-run
  • What now passes
  • What not verified + why

If fix narrow + confidence high, say so briefly. If verification partial, say so clearly.

Step 7: Capture Root Cause and Close the Loop

Use framework:context-anchoring Enrich behavior to preserve important parts of repair:

  • Bug summary: observed vs expected behavior
  • Root cause: what actually failed + where
  • Repair decision: why this fix chosen over alternatives
  • Protection added: regression test or executable reproducer now guarding behavior
  • Key files changed: path + purpose

If no context doc exists + fix exposed non-trivial design/domain lesson, suggest creating one.

Use framework:learning-harvest Harvest behavior. Session context: "bug investigation — root cause diagnosis and repair". Synthesize and propose cross-cutting patterns from this session — root cause categories, failure modes likely to recur elsewhere, boundary condition gaps. User confirms what enters the document.

After fix complete, recommend /review when change:

  • touches multiple layers
  • changes security-sensitive code
  • changes domain behavior
  • introduces non-trivial structural correction

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.