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[SLC]WeWise Labs · npx @wewiselabs/slc
The world's first spec-native language

Anlanguage & framework.

SLC is the world's first token-efficient, spec-native language for cognition. One command scrutinizes your idea like a principal engineer, then turns it into a validated spec tree; your own AI builds from it. No re-explaining. No drift. No wasted context.

Read the docs →
SLC mascot carrying a code folder
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Universal Compatibility

Your agent is the runtime. SLC is the framework it runs.

SLC doesn't replace the tool you already use — it directs it. The same framework drops into Claude Code, Cursor, Copilot, Codex or Antigravity and turns each one from a vibe-coder into a deterministic engineer.

Claude Code
Cursor
GitHub Copilot
Codex
Antigravity
Claude Code
Cursor
GitHub Copilot
Codex
Antigravity
Claude Code
Cursor
GitHub Copilot
Codex
Antigravity
FullAgentic + MCP — live docs, auto file-read, auto task execution.
PartialAgentic, no MCP — full structure, but no live-docs freshness.
BasicRaw chat LLM — paste the spec, keep every guarantee, lose MCP + automation.

The Diagnosis

0session memory

by default. Every new AI chat starts cold — no memory of your architecture decisions, no memory of your constraints, no memory of what was already built last time.

N+1re-explains

Stack, structure, conventions, boundaries. You explain the same project in every new session. The model listens, nods, then guesses anyway.

drift

without a spec. The AI fills every gap it finds — not with nothing, but with something plausible that quietly contradicts what you decided two sessions ago.

The Syntax

Every block is a contract. Nothing is implied.

spec/SPEC.slc
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# SLC - Spec Language for Cognition
# Every block is a contract between spec and machine.
 
@block INDEX root_index
priority: critical
intent: "Global router for execution"
failure_if_skipped: true
 
read_order:
- CONTEXT.md
- SECURITY.md
- ARCH.md
- tasks/task_index.md
@end
 
@block TASK auth_login
priority: critical
depends_on: [ARCH.auth, SECURITY.tokens]
memory_tier: hot
 
content:
- validate credentials against bcrypt hash
- issue RS256 JWT with 15min expiry
- set HttpOnly cookie, SameSite=Strict
@end
 
@block ARCH memory_system
scope: global
 
tiers:
hot: always loaded - SPEC, ARCH, SECURITY
warm: on-demand - task files, contracts
cold: indexed-only - historical, examples
@end
01

Deterministic read order

AI always loads context in the same sequence. No inference, no drift.

02

Explicit memory tiers

Hot / warm / cold. Nothing is loaded that isn't needed for this session.

03

Declared dependencies

Each task block knows exactly what context it requires before execution.

The Law

Memory.

Overrides.

Creativity.

SLC puts a MEMORY.md at the root of every project. Every decision, every constraint, every assumption — recorded and numbered. When the AI contradicts any of it, execution stops. That’s not a workaround. That’s the spec.

The Framework

Eight steps. Zero ambiguity.

Write the spec once. From then on every AI session reads it first and follows the same deterministic path — the framework decides what happens next, not guesswork.

01

Write CONTEXT.md

Project identity, constraints, tech stack, and deployment target — in SLC block format.

02

Define ARCH.md

Every system boundary, module, and cross-cutting concern declared as a named block.

03

Specify SECURITY.md

Auth patterns, session rules, trust boundaries — loaded in every AI session automatically.

04

Build task_index.md

All planned work as @block TASK entries with explicit priorities and dependencies.

05

Tag memory tiers

Decide hot/warm/cold per file. AI only loads what the current session needs.

06

Run SLC-aware agent

Agent reads the INDEX block first. Read order is deterministic. No guessing.

07

Verify CONTRACT.md

Every route, schema, and interface declared. Agent never deviates from the contract.

08

Ship with confidence

No unexplained rewrites. No invented patterns. Architecture is the law.

The Math

Most of your context window is context you've already explained.

Session #47 · Without SLC
Ok so here's the context for this session.
We're building a Next.js 14 / TypeScript SaaS platform.
Backend: FastAPI on Python 3.11, PostgreSQL.
JWT auth — access token 30 min, refresh 7 days.
Admin guard is separate from user auth middleware.
User model: id, email, hashed_password,
is_verified, is_active, is_admin, timestamps.
Downloads: pre-signed tokens, 15-min expiry.
Users must verify email before downloading.
Rate limiting: 100 req/min auth, 10 req/min tokens.
SlowAPI + Redis. Never expose is_admin publicly.
/api/admin routes live outside the main router.
Don't modify migration files directly.
Tailwind v4 syntax — bg-linear-to-b, not gradient.
Oh and the constraint from session #44 still applies...
[52 more lines of decisions you re-paste every time]

setup cost

~8,200

tokens · before you write a single line of code

Every session · With SLC
> read SPEC.md
✓ global router + read_order loaded
> read MEMORY.md
✓ 12 decisions anchored · drift protection active
> read ARCH.md
✓ 8 modules declared · boundaries clear
> "add the user profile endpoint"
→ /routers/profile.py · ARCH §User module existing auth guard · starting now

setup cost

~420

tokens · AI knows the rest already

↓90%context overhead

~90%

token reduction

3 tiers

hot / warm / cold

0

invented context

Builder Archive

Every SLC session leaves a record.

Not star ratings. Actual stories. Every builder who shipped with SLC files a .slc record. These are theirs, in their own words.

wewiselabs.slc

we as a team learned spec driven development, and honestly this was the first time we worked with SLC Framework, and it is no doubt the best spec framework we ever used, we can actaully see the track of our App and it's whole architechture.

daniyalfx.slc

I gave it one requirements file and it generated the full spec tree in a single pass. The read_order is the part that stuck with me. Every new session opens SPEC.md first and already knows the constraints, so I stopped re-explaining the project every morning.

marawhit.slc

MEMORY.md is doing the heavy lifting for me. My architecture decisions stayed put across a month of work instead of slowly drifting the way they used to. No more contradicting myself three sessions later.

owais_t.slc

Token usage per task dropped hard once it only loaded the depends_on sections. On a big repo that is the difference between a session that stays sharp and one that forgets the first half by the end.

fcardoso.slc

The frontend contract derived straight from the backend. My API and my UI did not disagree once, which honestly used to cost me a day or two every sprint.

nbrennan.slc

Setup is more work than just vibe coding, no point pretending otherwise. But what I shipped actually matched the plan, and for a real product that tradeoff is easy. I would not start a serious build without it now.

kosei.slc

I run it through Cursor and it just reads the spec files and follows them. No new tool to learn. My agent went from guessing to disciplined basically overnight.

wewiselabs.slc

we as a team learned spec driven development, and honestly this was the first time we worked with SLC Framework, and it is no doubt the best spec framework we ever used, we can actaully see the track of our App and it's whole architechture.

daniyalfx.slc

I gave it one requirements file and it generated the full spec tree in a single pass. The read_order is the part that stuck with me. Every new session opens SPEC.md first and already knows the constraints, so I stopped re-explaining the project every morning.

marawhit.slc

MEMORY.md is doing the heavy lifting for me. My architecture decisions stayed put across a month of work instead of slowly drifting the way they used to. No more contradicting myself three sessions later.

owais_t.slc

Token usage per task dropped hard once it only loaded the depends_on sections. On a big repo that is the difference between a session that stays sharp and one that forgets the first half by the end.

fcardoso.slc

The frontend contract derived straight from the backend. My API and my UI did not disagree once, which honestly used to cost me a day or two every sprint.

nbrennan.slc

Setup is more work than just vibe coding, no point pretending otherwise. But what I shipped actually matched the plan, and for a real product that tradeoff is easy. I would not start a serious build without it now.

kosei.slc

I run it through Cursor and it just reads the spec files and follows them. No new tool to learn. My agent went from guessing to disciplined basically overnight.

sanariaz.slc

The security file caught a hardcoded key before it ever reached git. I have used a lot of AI workflows and none of them treated redaction as an actual rule. Small thing that saved me a real headache.

kosei.slc

I run it through Cursor and it just reads the spec files and follows them. No new tool to learn. My agent went from guessing to disciplined basically overnight.

nbrennan.slc

Setup is more work than just vibe coding, no point pretending otherwise. But what I shipped actually matched the plan, and for a real product that tradeoff is easy. I would not start a serious build without it now.

fcardoso.slc

The frontend contract derived straight from the backend. My API and my UI did not disagree once, which honestly used to cost me a day or two every sprint.

owais_t.slc

Token usage per task dropped hard once it only loaded the depends_on sections. On a big repo that is the difference between a session that stays sharp and one that forgets the first half by the end.

marawhit.slc

MEMORY.md is doing the heavy lifting for me. My architecture decisions stayed put across a month of work instead of slowly drifting the way they used to. No more contradicting myself three sessions later.

daniyalfx.slc

I gave it one requirements file and it generated the full spec tree in a single pass. The read_order is the part that stuck with me. Every new session opens SPEC.md first and already knows the constraints, so I stopped re-explaining the project every morning.

sanariaz.slc

The security file caught a hardcoded key before it ever reached git. I have used a lot of AI workflows and none of them treated redaction as an actual rule. Small thing that saved me a real headache.

kosei.slc

I run it through Cursor and it just reads the spec files and follows them. No new tool to learn. My agent went from guessing to disciplined basically overnight.

nbrennan.slc

Setup is more work than just vibe coding, no point pretending otherwise. But what I shipped actually matched the plan, and for a real product that tradeoff is easy. I would not start a serious build without it now.

fcardoso.slc

The frontend contract derived straight from the backend. My API and my UI did not disagree once, which honestly used to cost me a day or two every sprint.

owais_t.slc

Token usage per task dropped hard once it only loaded the depends_on sections. On a big repo that is the difference between a session that stays sharp and one that forgets the first half by the end.

marawhit.slc

MEMORY.md is doing the heavy lifting for me. My architecture decisions stayed put across a month of work instead of slowly drifting the way they used to. No more contradicting myself three sessions later.

daniyalfx.slc

I gave it one requirements file and it generated the full spec tree in a single pass. The read_order is the part that stuck with me. Every new session opens SPEC.md first and already knows the constraints, so I stopped re-explaining the project every morning.

The Files

Two spec files. Every AI starts here.

SLC.md holds the syntax rules — the machine-readable grammar every agent understands. SLC universal structure.md is the universal framework your project maps to. Drop both in your root. The third file is your personal getting-started guide — read it once, never re-explain your setup again.

SLC Spec Files

SLC.md

SLC universal structure.md

SLC getting started guide.md

Click the folder to open

03 · The Architecture

Spec Graph

This portal was built with SLC.
Scroll to see the spec that built it.

03 · Architecture — SLC Spec Graph

Click node to open tree · Drag to explore
Root
Spec dirs
Files
Tasks

SLC vs the Field

Every other system leaves it to the agent. SLC builds it into the framework.

15 capabilities that make an AI build deterministically instead of guessing. Below: which are built into each system, which are partial, which are missing entirely.

[SLC]SLC
15/15
Spec Kit
2/15
Claude Code
0/15
GitHub Copilot
0/15
Cursor
0/15
AGENTS.md
0/15
Built inPartial / by conventionAbsent
Claude CodeCopilotCursorAGENTS.mdSpec KitSLC
Spec structure
Typed, machine-parseable block grammar
Explicit per-item priority
Separate ARCH / CONTRACT / TASKS artifacts
Single source of truth for task status
Dependencies & determinism
Dependency graph (depends_on)
Mandatory read-order routing
Conflict-authority hierarchy
Frontend derives from backend contract
Context economy
Context tiering (HOT / WARM / COLD)
File-split protocol with index
Live-docs freshness rule (MCP)
Anti-hallucination memory anchor
Integrity & safety
Mandatory security-redaction law
Hash / version drift detection
Structured diagnostics / error codes
Built in0000215

15 of 15, built in. The nearest rival manages 2. On structure, SLC isn't ahead of the field — it's a different category.

Honesty note: “built in” means defined by the SLC format. The structural rows (grammar, references, split protocol, contract derivation, redaction) are mechanically enforced today by slc doctor; hash/version drift detection is defined in the spec and lands with the v0.3 validator.

The Verdict

Spec first.

Code second.

Memory anchored.

No drift.

That’s SLC.

Read the docs
WeWise Labs | 2026