EvidenceContext quality
Bigger Context Windows Still Need Control
Why larger windows still need ranking, scoping, and retrieval discipline.
Aug 11, 2025
Contextus
Control what AI agents see, do, and prove.
Contextus compiles the right context, applies policy before risky tool calls, pauses for human approval when needed, and keeps audit-ready proof across MCP and editor-native workflows.
Built for AI engineering teams, platform teams, and teams using MCP or editor-native agents in real environments.
Governed context compilation
Compile the right repo, docs, and task history before the agent acts.
Risky tool approval
Classify write, delete, network, and credential-use actions before execution.
Audit log
Record the action, decision, actor, and rationale in one reviewable trail.
Eval-backed workflow
Keep policy and outcome proof together for engineering and security review.
What breaks first without control
Bigger context windows help, but they do not solve what happens when an agent can actually take action on your behalf.
Wrong context reaches the agent
The critical file, ticket, or policy note never makes it into the working set.
Risky tool calls run on autopilot
Write, delete, network, and credential-using actions need more than a best guess.
No one can prove what happened later
Without approvals, audit logs, and eval evidence, review becomes memory and debate.
Compile + Govern + Approve + Prove
The strongest product proof is operational, not conceptual: a risky action appears, approval is required, and the audit trail is written.
Compile
Context that stays on task. Contextus selects the files, docs, policies, and task history that matter, so agents act with the right information instead of a bloated prompt.
Govern
Apply policy before risky tools run so the workflow stays constrained.
Approve
Pause high-risk actions until a person decides to allow or deny them.
Prove
Keep audit history and eval evidence together for later review.
1. Compile
Working context gathered
Pull the files, docs, and task history that actually matter before the agent acts.
Customer-impacting change
Release policy
Recent deployment history
2. Govern
Risk classified
Action: delete production databaseCritical risk
Policy: Requires human approval.
3. Approve
Approval required
The agent wants to delete production data. This action is blocked until reviewed.
4. Prove
Audit entry written
- Agent
- Deploy Bot
- Decision
- Denied
- Reviewer
- Platform lead
- Reason
- Destructive action blocked
For teams past the demo phase.
When an agent can write code, call tools, or affect customer-facing systems, the question changes from “Can it do the task?” to “Can we control and prove what it did?”
AI engineering teams
Building agent workflows that need reliable context, evals, and safety checks before broader rollout.
Platform teams
Defining policies, approval paths, and audit trails for internal agent tooling.
Developer-tool teams
Embedding agents into IDEs, MCP tools, CI workflows, and custom engineering environments.
Pricing
Most teams adopt Contextus when shared approvals, audit export, and Agent Passports start to matter — that is why Team is recommended.
Free
$0/month
For exploring governed agent workflows
Try Compile, Govern, Approve, Prove
Limited IDE/MCP tools
Starter workflow templates
7-day data retention
Builder
$19/month
For individual developers validating governed agent workflows
Personal Action Control
Personal audit history
Basic proof export
Policy Editor
Team
Recommended$99/month
For teams piloting governed agents
Shared Action Control
Approval workflows
Audit export
Agent Passports preview
Enterprise
Custom
For larger organizations with security needs
Advanced approvals
Custom retention
SSO / SAML / SCIM
Security review
Writing about governed agents
Field notes about Action Control, approvals, and proof — the parts of governed agent workflows that need the most explaining today.
EvidenceAction Control
Why AI Coding Agents Need Approval Gates
What changes when an agent can write, delete, or deploy — and how Action Control responds.
Coming soon
EvidenceProof
How Eval-Backed Proof Works
Combining policy, approvals, and eval results into evidence teams can actually review.
Coming soon