cold agent
16
searches before a reliable plan
16 repo searches before the agent can plan
Cold context opens only 5 of 76 answer-key files
Rationale lives in a previous chat
Agent-neutral project layer
Shared Project Intelligence for Claude Code, Cursor, Codex and your team.
Start every agent session with what changed, why it matters, what it impacts and what to do next.
Your agents change. Your project intelligence doesn't.
Less rediscoveryFaster handoffsBetter decisionsSafer edits
app.snipara.com/project
agent › new session
↳ snipara.start_work_brief()
✓ what changed: invite billing behavior
why: LINEAR-142 · active decision
✓ impact: callers → billing → 3 tests
✓ next action: run migration verification
confidence high · 17 similar changes
→ safe to proceed
continuity layer
confidence
Works with Claude Code, Cursor, Codex, VS Code and any MCP-capable agent.
Agent-neutralProject-owned memorySSO, audit and SLA on Enterprise
60-second demo
From 16 searches to 3 artifacts before the first edit.
A small toy repo shows the problem without signup: same billing bug, same agent, but Snipara loads the brief, impact and verification before the model touches code.
with Snipara
3
artifacts before the first edit
Start Work Brief: what changed and why
Code Graph impact: callers, files and tests
Verification card: go / stop before editing
why Snipara exists
Project intelligence, not one agent's private memory.
Claude Code, Cursor, Codex, humans and CI should start from the same decisions, handoffs, impact evidence and verification signals. Snipara keeps that state in one governed project layer, while each agent keeps its own runtime.
Agent platforms run work. Snipara carries the project.
A shared layer for the context, decisions and proof that should survive every tool, model and session.
Agent platforms
Snipara
Run agents
Give every agent the same project-owned context
Optimize one runtime
Work across Claude Code, Cursor, Codex and custom agents
Automate tasks
Preserve decisions, handoffs, impact and proof between sessions
Without Snipara
Cold start, every session
The agent rescans the repo and reconstructs the task from raw files.
Decisions evaporate
Yesterday's rationale lives in old chats and one developer's memory.
Blind to parallel work
Another human or agent edits the same surface without warning.
With Snipara
Starts with what changed and why
Start Work Brief: changes, decisions and rationale loaded first.
Impact and next action
Blast radius, prior outcomes and caveats rank the next check.
Guards before risky edits
Coordination, active work state and consistency checks say go / stop.
measured replay
The business outcome first, the numbers underneath.
Less rediscovery
81% fewer cold searches
16 searches replaced by 3 artifacts
Cold replay needed 16 task-derived searches before planning. The assisted replay started with Start Work memory, workflow plan and impact context.
Cold handoff risk exposed
5 of 76 files
found in the first cold context set
The answer key had 76 changed files. The cold handoff surfaced only 5 of them first, making the missing context visible.
Key surfaces before edits
7 of 7 surfaces
visible before edits
The assisted replay surfaced all answer-key categories: web routes, services, dashboard, CLI, MCP, docs and deploy/config.
Proof before the next edit
go or stop
guard before the next edit
Caveats and verification signals travel with the handoff before the next change.
These are controlled replay measurements, not universal ROI claims. Time saved, regression reduction and rework avoided should be reported only when the workflow trace captures them. Based on controlled replay of real agent work. See methodology.
Workflow continuity for AI coding agents
Connect an agent, load the brief, inspect code impact, verify the work, then feed the outcome back into the next run.
Companion lifecycle
The operational layer inside the agent loop.
Companion runs the lifecycle inside the loop: start work, record phase commits, hand off context, resume cleanly and carry judgment evidence forward.
Connect
Any agent enters the same project-owned continuity layer.
Claude Codeconnected
Cursorconnected
Codexconnected
Start Work Brief
What changed, why it matters, impact and next action before the first edit.
what changed
billing invite behavior
why
active product decision
next action
inspect impact first
Code Impact
Callers, files, risky paths and likely checks are surfaced before code changes.
routeservicetests
risk level
LightMediumHigh
3 callers2 files
Verify
The agent gets required checks, confidence, caveats and proof before proceeding.
billing test
type-check
auth guard
Outcome
Phase commit, handoff and judgment evidence feed the next session.
phase commit
decision + caveats
handoff
next agent context
judgment
readiness + evidence
↺05 loops back into 01
Snipara turns context into next-action guidance.
Context is evaluated against decisions, historical impact, observed outcomes and reason-code calibration.
code graph · impact chain
// changed: createWorkspaceInvite()
impact: invite flow → billing policy → permission boundary
tests: workspace-invites · billing-seats · permissions-boundary
history: 17 similar changes · 4 regressions
decisions: LINEAR-142 · billing rounding #88
⚠ missing: production config check
snipara guidance
$ snipara-companion brief
✓ next action: run migration verification
confidence: HIGH
caveat: limited evidence in this module
✓ safe to proceed: no owner overlap
Snipara Graph
Callers, imports, blast radius and the historical consequences of similar changes.
Recommendations Informed by Outcomes
Advisory next steps with confidence, evidence, counter-evidence and caveats.
Drop it into the stack you already run
Open primitives and protocols, wired to the tools your team already lives in.
common objection
Why bigger context windows do not solve this.
A larger window lets the model read more at once. It does not decide what is current, which decision is canonical, what the change impacts, or which checks make the edit safe.
Use both: give the model enough room to reason, but let Snipara supply the curated project state, source authority, impact graph and verification evidence.
Bigger window
Project intelligence
Can fit more files in one prompt
Selects the right facts, decisions and caveats for the current task
Still mixes current truth with stale notes and old chats
Uses reviewed source authority so the agent knows what to trust
Does not compute blast radius or verification work
Adds Code Graph impact, handoffs, proof and required checks before edits
Give any AI agent project intelligence and workflow continuity
Start free. Scale when your agents do. Billed annually, save 20%.
Most popular
Pro
$39.20/mo annually
- 10 projects
- 10,000 queries / mo
- Impact + symbol cards
- What Changed For Me
Team
$119.20/mo annually
- 5 seats · unlimited projects
- 50,000 queries / mo
- Team Sync briefs
- Analytics & governance
Enterprise
$439.20/mo annually
- 20 seats included
- 500k queries / mo
- SSO · audit · SLA
- Rollout support