Intent in-tca-synthesize

TCA synthesize: cross-component deduplication, priority classification, and fix batch ordering

install
source · Clone the upstream repo
git clone https://github.com/matthewsinclair/intent
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/matthewsinclair/intent "$T" && mkdir -p ~/.claude/skills && cp -r "$T/intent/plugins/claude/skills/in-tca-synthesize" ~/.claude/skills/matthewsinclair-intent-in-tca-synthesize && rm -rf "$T"
manifest: intent/plugins/claude/skills/in-tca-synthesize/SKILL.md
source content

TCA Synthesize

Performs cross-component synthesis of all completed audit findings. Deduplicates violations by root cause, classifies into 5 priority tiers, and produces a prioritized remediation backlog.

For reference:

intent/docs/total-codebase-audit.md

Procedure

1. Read all socrates.md files

Read every completed WP's

socrates.md
. If any component WPs are incomplete, stop and run
/in-tca-audit
first.

2. Aggregate statistics

Build a per-WP summary table:

| WP    | Component | Total | High | Medium | Low |
| ----- | --------- | ----: | ---: | -----: | --: |
| WP-01 | {name}    |     X |    X |      X |   X |

...
| **Sum** | **All** | **T** | **H** | **M** | **L** |

3. Rule distribution

Count violations per rule across all WPs:

| Rule | Name            | Count | Dominant WPs   |
| ---- | --------------- | ----: | -------------- |
| R6   | Highlander Rule |   ~XX | All / specific |

...

This reveals systemic issues (rules violated everywhere) vs localized issues (one bad module).

4. Cross-cutting deduplication

The most important synthesis step. Cluster violations by root cause and fix, NOT by rule number:

Deduplication signals:

  • Same function name reported in multiple WPs
  • Same root cause (e.g., "no shared utility module")
  • Same fix recommended across WPs

Split signals (do NOT merge these):

  • Same rule but different data types (e.g., Map.get on struct vs Map.get on plain map)
  • Same pattern but different contexts requiring different fixes
  • Same function name but genuinely independent implementations

Benchmarks:

  • Expect 40-60% dedup rate on large projects
  • Projects with strong existing architecture have lower dedup rates

5. Priority classification (5 tiers)

Classify each unique violation into one of five tiers:

TierNameCharacter
P0Bugs and crash risksIncorrect behavior or crashes in production
P1Highlander duplicationsCross-cutting code duplication
P2aMechanical quality gapsBulk-fixable, no design decisions needed
P2bMinor refactoringRequires design decisions, single-module
P3Style and conventionLowest impact mechanical fixes

P0 examples: bare

=
match on fallible calls,
String.to_atom
on user input, debug artifacts in production paths, non-exhaustive
with
clauses

P1 ranking criteria: copy count, inconsistency risk, fix scope

P2a examples: missing

@impl true
, missing SAFETY comments, missing
@doc
/
@spec
, unambiguous boolean operator fixes

P2b examples: thick coordinator extraction, multi-head function conversion, component extraction

P3 examples: naming conventions, pipe operator adoption, access control tightening

6. Fix batch ordering

Group into batches:

Batch A: P0 critical bugs (small, targeted, test after each)
Batch B: P1 highest-impact Highlander fix (extract shared module)
Batch C: P1 second-highest Highlander fix
Batch D: P1 domain-scoped dedup (fixes within one domain)
Batch E: P2a mechanical fixes (grep-and-fix in bulk)
Batch F: P2b thick coordinator refactoring (one per batch)
Batch G: P2b multi-head conversions (incremental)
Batch H: P3 style fixes (batch by rule, one commit per rule)

Interleaving: P2a can be interleaved with P1 since they touch different files. P2b should wait until P1 shared modules exist.

7. Polyglot two-pass synthesis

For polyglot projects:

  1. Within-ecosystem pass: Synthesize findings per ecosystem (Elixir violations, Rust violations, etc.)
  2. Cross-ecosystem pass: Look for X-rule violations and patterns that span ecosystems (e.g., API contract mismatches, shared Highlander patterns across language boundaries)

8. Present for review

Before writing the synthesis, present key findings to the user:

  • P0 items: any false positives?
  • P1 priority order: which Highlander fixes matter most?
  • P2b scope: which refactorings are worth doing now vs deferring?
  • Overall dedup rate: does it match expectations?

9. Write synthesis

Write the complete synthesis to the final (synthesis) WP's

socrates.md
:

  • Aggregate statistics table
  • Rule distribution table
  • Deduplicated violation list with priority classification
  • Fix batch ordering with dependency notes
  • False positive notes (violations reviewed and rejected)

10. Commit

git add WP/{synthesis}/socrates.md
git commit -m "audit: synthesis -- {X} unique violations across {N} WPs"

Proceed to review (Phase 3), then

/in-tca-remediate
for execution.

Important Notes

  • Cluster by root cause and fix, not by rule number
  • Split clusters when same rule has different data types or contexts
  • The P2a/P2b distinction matters: mechanical fixes are parallelizable, refactoring is not
  • Always present synthesis for user review before remediation
  • For polyglot: run two-pass synthesis (within-ecosystem then cross-ecosystem)