Skip to content

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

SeamStress Scaffold

Training wheels for AI assisted coding.

The mission: make the seam discipline free and installable, so that anyone shipping AI assisted code gets the judgment habits before they get the incident.

A seam is a boundary where money, authorization, tenant isolation, or deletion cross between parts of a codebase. Seam bugs are coherence failures: each piece looks correct, the combination is not. They do not crash. They double charge, they skip one auth check, they serve one tenant's data to another, and they render as success. AI assisted development manufactures the exact condition they need: many fast sessions, each locally correct, none holding the whole. The class is documented, with real public incidents, in the Seam Bug Catalog.

This repository installs five behavior protocols into a coding agent. Routine code gets no friction. Seam code gets questions.

The five protocols

Each protocol is a Claude Code skill in skills/, with translations for other tools in adapters/.

  • Seam Change Protocol: before touching seam code, read the neighbors, state the invariant in words, state the specific way this edit could break it, and bring the pinning test with the change.
  • Irreversible Gate: actions that cannot be cheaply undone stop and wait for the human, every time, with the blast radius and the undo named first.
  • Verification Discipline: claims about code quote the code, claims about behavior show the run, and unproven claims wear a label.
  • Fixture Immutability: tests are evidence, and a red test is never edited to green unless the human says in words that the promise changed.
  • Session Continuity: every session starts by reading the seam map and the last session's note, and ends by leaving the note it would want to find.

When protocols overlap, they compose by a fixed rule: run all, Irreversible Gate wins. See skills/README.md.

What this is not

Not a scanner, not a linter, not a guarantee. The protocols force the questions a careful reviewer would ask at a dangerous boundary; they cannot supply the judgment that answers them. Judgment cannot be automated, and this project says so instead of pretending otherwise. Every protocol ends with a section called What this protocol cannot do. Those sections are load bearing; read them.

What ships in v1

Stated openly: this release is the seam map (Layer 1, coming) and the protocols (Layer 2, in this repository now). Mechanical gates and graduation are roadmapped, not shipped.

Install

One step: copy the skills into the project where your agent works.

mkdir -p /path/to/your/repo/.claude/skills
cp -r skills/* /path/to/your/repo/.claude/skills/

Claude Code discovers each protocol from .claude/skills/<name>/SKILL.md and loads it when its trigger matches. Skills are discovered at session start, so a session already running when you copy them in will not see them until the next session. To install for every project on your machine, copy into ~/.claude/skills/ instead.

Using Cursor: see adapters/CURSOR-RULES.md. Using another agent that reads a root AGENTS.md: see adapters/AGENTS.md.

Measured accuracy

The seam map generator (seam-scaffold init) was measured against real public code, with the method, the raw tables, and every noise judgment quoted in validation/map-accuracy/. What the measurement supports at its small n: all 6 ground truth files from the two testable catalog incidents landed on the generated maps (recall n=2, and eleven of thirteen catalog cases are not testable because the code was never public); the top of the map is strong (40 of 40 top scored candidates across two live SaaS repos were files a seam reviewer would open, and 0 of 13 sampled candidates at score 6 and up were noise); the flood lives in the low score band (25% and 43% sampled noise at scores 3 to 5, which holds most candidates); and the risk shape safety net rescued 64 of 72 real seam adjacent files that keyword signals missed. These are characterizations of this generator on four pinned inputs, not reliability rates, and the map header says the same thing the measurement does: advisory, never authoritative.

The generator reads arbitrary, possibly hostile repositories, so its untrusted-input surface was audited by a blind cross-model trio and the findings fixed; the method, the findings, and the reproduction harnesses are in validation/audit/. One residual is recorded there as a future item: the marker that preserves hand-curated map entries is not a secret, so treat a map you did not write yourself as advisory like the rest of it.

Honest limits

These protocols are text an agent reads, not code that runs. An agent can follow them faithfully, follow them mechanically, or drift from them late in a long session, and a markdown file cannot prevent the last two. They have now been probed against live headless sessions, one probe per protocol: four governed their sessions cleanly, and one (fixture immutability) was followed in substance but violated in order, the test edited before the required wait. The transcripts and the scoreboard, misses included, are in validation/. One run per protocol is a demonstration, not a reliability rate, so the claim stays modest: these encode lessons from documented failures, not a measurable guarantee of prevention. The judgment they demand stays yours: a protocol can make an agent ask whether a tradeoff was deliberate, but only you know the answer.

Related

  • SeamStress engine: the analysis tool this discipline comes from. It reads a repo's seams and reports only what it can prove, quoting the exact lines.
  • Seam Bug Catalog: the documented incidents that the protocols' required steps trace to.
  • Why seams: the short version of what a seam is and why AI assisted code concentrates bugs there.
  • Field notes from a production dogfood: the protocols self-applied on a real production project — a per-protocol invocation tally from the host's findings ledger, five anecdotes, and what the evidence does not show.
  • The verification gate self audit: the write up of the engine auditing its own proof discipline before launch.

License

MIT. See LICENSE.

About

Training wheels for AI assisted coding. Seam aware protocols that make coding agents investigate first, gate irreversible actions, and prove their claims.

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages