Define. Verify. Enforce.
what “done” means for AI work.
Turn AI plans into structured contracts. Verify completion with real evidence. Enforce it at runtime — not after the fact.
Works with Claude Code · Codex · Cursor · Windsurf
AI agents are powerful — but they can't prove their work is done.
AI systems can produce useful output, but you can't always see what they used, what changed, or whether the result is correct.
Context is scattered
Instructions, source material, and past decisions live across repos, docs, chat windows, and hidden dashboards. There is no single place to understand what an agent depends on.
Changes are hard to inspect
When an agent modifies something, you don't know what changed or why. No diff. No audit trail. No proof the change was correct.
There is no way to verify completion
Agents say "done" constantly. But there is no system that proves the work is actually complete, correct, and compliant with what was agreed.
Agents can say “done.” But there is no system that proves it.
Filepad turns AI work into something that can be verified.
Filepad introduces a system of active contracts — structured definitions of what must be true before work is considered complete.
Agents work against contracts
Every task is defined as a structured agreement with rules, checks, and completion criteria.
Evidence verifies the work
Commands, search results, file state, and external sources report what is true. Status is derived from evidence, not declared by the agent.
Completion is enforced
Work is only done when the contract is satisfied — not when the agent says so. Failing checks block completion.
Work is not just stored. It is evaluated.
Active contracts define what “done” means.
A structured YAML artifact that declares rules, checks, and completion conditions. Parsed, validated, and continuously verified — not just decorative text.
kind: filepad.agent_contract.v1
name: PDF Highlight Hard Cut
checks:
- id: typecheck
type: command
command: pnpm -C apps/backend typecheck
expect_exit_code: 0
- id: no_legacy_code
type: search_absent
query: pdf_highlights.draft_by_query
paths:
- apps
- packages
done_when:
- typecheck
- no_legacy_codeAgents cannot reliably claim completion when checks are failing, stale, or unverified. Filepad enforces the difference between output and proof.
From intent to verified outcome.
Define the contract
Turn plans, tasks, or specifications into structured contracts with checks and completion rules.
Agents execute work
External agents — Claude, Codex, Cursor, Windsurf — operate within the workspace and propose changes against the contract.
Filepad verifies
Watchers, checks, and external evidence determine what is passing, failing, or stale. Status is derived, never self-declared.
Completion is enforced
Work is only complete when the contract is satisfied — not when the agent says it is. Failing checks block completion.
Runtime enforcement, not just dashboards.
Through runtime hooks and verification systems, Filepad can block disallowed actions, mark checks stale when reality changes, require evidence before completion, and prevent agents from claiming “done” prematurely.
Filepad is not another IDE. It is the accountability layer for AI-driven work.
Block disallowed actions
Runtime hooks prevent agents from mutating files or running commands outside the contract.
Mark checks stale
When reality changes — a file is modified, a branch updates — checks go stale and require re-verification.
Require evidence
Completion is not declared. It is proven. Every passing check must be backed by evidence from a trusted source.
Prevent premature done
Agents cannot claim completion while checks are failing, stale, or unverified. The contract enforces the gate.
A workspace where AI work is visible and enforceable.
See what agents did, what changed, and what still needs to be proven.
Connected runtimes
Review before merge
Passing / failing / stale
Every change tracked
Derived, not declared
Works with your existing AI tools.
Structured outputs, not just files.
Agents can produce documents, structured data, spreadsheets, and flow diagrams. All outputs are reviewable, versioned, and tied to contract verification.
Built for people who operate AI systems.
Running AI workflows that need to be verified, not just trusted.
Integrating agents into production workflows with accountability and evidence.
Managing multiple client systems where proof of completion matters.
Building agent-driven products that need structured verification and enforcement.
Simple. No usage-based surprises.
Start free. Scale when you need more agents or workspaces.
Try Filepad and see if it works for you.
- ✓1 workspace
- ✓File tree + editor + diff review
- ✓FilepadAI assistant
- ✓Agent connections via MCP
- ✓Community support
- —No shared workspaces
- —No API access
For operators running real agent workflows.
- ✓3 workspaces
- ✓Shared workspaces
- ✓File tree + editor + diff review
- ✓FilepadAI assistant
- ✓Agent connections via MCP
- ✓API access
- ✓Priority email support
- —Limited automation controls
For teams and power users who need advanced automations.
- ✓Unlimited workspaces
- ✓Shared workspaces
- ✓File tree + editor + diff review
- ✓FilepadAI assistant
- ✓Agent connections via MCP
- ✓API access
- ✓Advanced automation controls
- ✓Priority support
For organizations that need custom limits and dedicated support.
- ✓Everything in Pro Plus
- ✓Shared workspaces
- ✓Custom workspace limits
- ✓Dedicated support
- ✓Custom onboarding
Stop trusting AI output.
Start verifying it.
Filepad is the accountability layer for AI-driven work. Define what done means, verify it with evidence, and enforce completion.
Free to start · No credit card required · Cancel anytime