Imported from aimasteracc/tree-sitter-analyzer (tree_sitter_analyzer/skills/tsa-edit-then-verify/SKILL.md). Install upstream with npx skills add aimasteracc/tree-sitter-analyzer --skill tsa-edit-then-verify. Copyright stays with the author.

tsa-edit-then-verify — The full edit loop, scoped not full-suite

Source of authority. From docs/agent-tooling-gap-report.md line 58:

Every feature update must run the self-hosted workflow: edit action=safe before risky edits, health action=file on changed files, edit action=impact after edits, its reported verification_command, then the full default suite when risk remains.

This skill is the executable form of that rule. tsa-edit-safety only covers Phase A (the pre-edit gate). This skill covers A + B + C end-to-end and is the canonical replacement for the global verify skill (which runs the full ~5-minute suite every time).

When to use vs. not

Use when you're about to edit (or just edited) a real code file in this repo and the change is more than a 1-line cosmetic fix. The smaller the diff, the bigger the win — full pytest is ~5 min, scoped verification is typically 30-60s.

Don't use for:

• One-line typo in a doc/comment (no Python AST impact)
• Pure markdown / README edits (no symbol-level risk)
• File you're creating from scratch with no callers yet
• Read-only exploration

Why this exists (vs. verify skill)

The scoped command targets only the tests reachable from the changed symbols, via the AST call-graph. That's the whole point — edit action=impact returns a verification_command that's narrower than pytest -q but still covers the blast radius the AST sees.

Procedure

Phase A — Pre-edit (1 parallel MCP batch)

Call these in ONE message (parallel tool use):

1. edit action=safe with file_path: "<file>" and edit_type: "<refactor|add_feature|fix_bug|rename>"
2. health action=file with file_path: "<file>" — record the grade. This is your baseline.
3. (Optional, only if file is unfamiliar to you in this session) project action=smart with file_path: "<file>" and query: "<what you intend to change>"

Gate the verdict. From edit action=safe verdict:

• UNSAFE → STOP. Surface the risk_factors, ask the user how to proceed. Do not edit.
• CAUTION → narrow your scope. Write a failing test first if there isn't one for the behavior you're changing.
• REVIEW → write a test before the edit if risk_factors mentions "no tests nearby".
• SAFE → proceed to Phase B.

Persist the baseline grade. Note health action=file grade and health action=file score in your scratch — you will diff against these in Phase C.

Phase B — Edit (out of skill scope)

This is where the LLM actually does the work — Edit / Write / MultiEdit tool calls. The skill's only job here is to remind you: keep the diff focused. Large diffs make Phase C's scoped command less reliable (and may bump you into "full suite" territory at step 7).

If you find yourself making >100 lines of changes across >3 files, pause and reconsider whether this is really one task or three.

Phase C — Post-edit verify (1 parallel MCP batch, then Bash)

After your last edit, call these in ONE message (parallel tool use):

4. health action=file with file_path: "<file>" again → diff against Phase A baseline. Grade MUST NOT regress. (B→C is a regression. A→A is fine. F→D is improvement.)
5. edit action=impact with mode: "staged" (or mode: "branch" if you haven't staged) — returns verification_command, pytest_command, queue_ledger, risk_remains flag.

Then sequentially via Bash:

6. Run the exact verification_command returned by step 5. This is the scoped command. Example shape:

   uv run pytest tests/unit/test_health_scorer.py tests/unit/test_file_health_smells.py -q

   Expect 30-60s. If it fails, fix and re-run from step 4.

7. Only if edit action=impact risk_remains == true (or grade regressed in step 4, or impact reports cross-module reach), run the full suite:

   uv run pytest -q

   This is the ~5-minute fallback. Use it sparingly — the whole point of step 6 is to avoid this when the AST says we don't need it.

If step 7 also passes, you're done. Report verdict, grade delta, and the command you ran.

Worked example: editing tree_sitter_analyzer/health_scorer.py

This file is 891 lines, complex, and has many callers — a realistic "feature update" target. Suppose you're adding a new dimension to the health-grading rubric.

Phase A trace

PARALLEL BATCH (one message):
  → edit action=safe file_path="tree_sitter_analyzer/health_scorer.py" edit_type="add_feature"
  → health action=file file_path="tree_sitter_analyzer/health_scorer.py"
  → project action=smart file_path="tree_sitter_analyzer/health_scorer.py"

Returned:
  edit action=safe:  verdict=REVIEW
                 risk_factors=[{factor: "hot_zone", detail: "mod_count_30d=7"}]
                 verification_command="uv run pytest tests/unit/test_health_scorer.py -q"
  health action=file: grade=B, score=84, weakest=complexity   ← BASELINE
  project action=smart: top 3 callers = [health action=project, health action=file, cli/__main__]

Verdict is REVIEW + hot_zone — write a test for the new dimension first.

Phase B (out of scope)

You write the failing test, then edit health_scorer.py to add the new dimension. Diff is ~40 lines.

Phase C trace

PARALLEL BATCH (one message):
  → health action=file file_path="tree_sitter_analyzer/health_scorer.py"
  → edit action=impact mode="staged"

Returned:
  health action=file: grade=B, score=82, weakest=complexity   ← B→B, no regression ✓
  edit action=impact:
    verification_command="uv run pytest tests/unit/test_health_scorer.py
                          tests/unit/test_file_health_blocks.py
                          tests/unit/test_file_health_smells.py -q"
    pytest_required=true
    risk_remains=false   ← scoped command is sufficient
    queue_ledger=[{file: health_scorer.py, symbols: [grade_file, _compute_dim]}]

THEN Bash (sequential):
  $ uv run pytest tests/unit/test_health_scorer.py \
                  tests/unit/test_file_health_blocks.py \
                  tests/unit/test_file_health_smells.py -q
  ... 42 passed in 38.1s ✓                                    ← ~38s, scoped

  (risk_remains=false → skip full suite)

Done. Total verify time: ~38s vs. ~5 min for uv run pytest -q. That's an ~8× reduction on the verify step alone, and you still ran the tests the AST said were reachable from your edit.

Phase D — Doc Sync (gate before commit)

If your edits touched any of these surfaces, the corresponding codemap MUST be updated in the SAME commit:

Step D1 — Detect surface change

git diff --cached --name-only
git diff --cached -- tree_sitter_analyzer/mcp/_tool_registry.py | grep -E '^\+.*\("(codegraph_|[a-z_]+",)'

Step D2 — If a surface changed, run the codemap skill

Invoke /update-codemaps — it scans the registries and regenerates the codemap section. Alternatively dispatch the global doc-updater agent for deeper sync (also touches README/AGENTS.md).

Step D3 — Verify with the hard gate

scripts/codemap-sync-check.sh runs automatically as a pre-commit hook and BLOCKs the commit if a surface change is staged but its codemap isn't. To dry-run locally:

bash scripts/codemap-sync-check.sh
echo "exit=$?"  # 0 = pass, 1 = block

Escape hatch (intentional rename without semantic change): SKIP_CODEMAP_SYNC=1 git commit .... The pytest test_registered_mcp_tools_have_codemap_parity is the safety net that catches abuse in CI.

Why Phase D exists

The hook (Phase D's hard gate) only catches what's staged at commit time. Phase D in this skill catches drift earlier — at edit-time the agent already knows which codemap to update, so the user never sees the commit-time block. The hook is the fallback for forgotten cases / non-AI commits.

CLI equivalents (when MCP is unavailable)

Run pre-edit (Phase A) in parallel:

uv run tree-sitter-analyzer tree_sitter_analyzer/health_scorer.py \
  --safe-to-edit --edit-type add_feature --output-format json
uv run tree-sitter-analyzer tree_sitter_analyzer/health_scorer.py \
  --file-health --output-format json
uv run tree-sitter-analyzer tree_sitter_analyzer/health_scorer.py \
  --smart-context --output-format json

Run post-edit (Phase C):

uv run tree-sitter-analyzer tree_sitter_analyzer/health_scorer.py \
  --file-health --output-format json                          # grade diff
uv run python -m tree_sitter_analyzer --change-impact \
  --change-impact-mode staged --output-format json            # gets verification_command
# then copy-paste the verification_command from the JSON output and run it

Verdict cascade (Phase A gate)

Grade-regression rule (Phase C step 4)

Compare health action=file grade before vs. after:

A grade regression is a soft fail — surface it to the user, don't auto-abort. Some edits legitimately worsen one dimension while improving overall behavior. Let the user decide.

When to escalate to full pytest (Phase C step 7)

Run uv run pytest -q (full suite, ~5 min) only when ANY of these is true:

• edit action=impact risk_remains == true
• Grade regressed in step 4 (A→B or worse)
• Edit touched any of: BaseMCPTool.__init__, PathResolver, SecurityValidator, plugin registry, cli/__main__.py, mcp/server.py
• Edit crossed >3 files
• edit action=impact queue_ledger shows cross-module reach (impact crossing top-level packages)

Otherwise the scoped verification_command from step 6 is the official verify gate — no need to burn 5 minutes.

Anti-patterns

• Skipping Phase A because "it's just a small change" — Phase A is ~3s and catches UNSAFE constraint violations that would waste your Phase B effort.
• Running pytest -q immediately in Phase C without first calling edit action=impact — defeats the whole purpose of this skill. The scoped command is the point.
• Ignoring grade regression in Phase C step 4 — a B→C regression on a hot-zone file is a real signal even if tests pass.
• Running each phase in serial MCP calls — Phase A is one parallel batch, Phase C is one parallel batch. Don't make 6 sequential calls.
• Treating verification_command as advisory — it's the literal command to run. Don't paraphrase it or "improve" it.

Decision surface returned

phase_a:
  verdict: SAFE | REVIEW | CAUTION | UNSAFE
  baseline_grade: A | B | C | D | F
  baseline_score: 0-100
  risk_factors: [...]
phase_c:
  current_grade: A | B | C | D | F
  current_score: 0-100
  grade_regression: bool
  verification_command: <exact bash line>
  verification_result: PASS | FAIL
  risk_remains: bool
  ran_full_suite: bool
  total_verify_seconds: <int>
verdict: PASS | FAIL | NEEDS_REVIEW

See also

• tsa-edit-safety — Phase A alone, when you only want the gate verdict
• tsa-health-watch — grade tracking over time (daemon)
• verify (global) — full-suite fallback for pre-commit
• CLAUDE.md § Build & Test — the project rule this skill implements
• docs/agent-tooling-gap-report.md line 58 — the source-of-authority mandate