Argus captures every session of your users across your team or organization, then reads across thousands of them at once — surfacing where skills are holding, where they're quietly breaking, and which patterns are pointing at the next thing you should build.
Magic-link sign in. No password. Free during alpha.
Sessions captured
Cost
Tokens
Active users
Errors
Spot checks
Recent sessions
workspaceLive preview · Argus dashboard, one workspace
The problem
Claude Cowork's built-in telemetry tells you a skill was invoked. It can't tell you whether it worked, whether the user took the answer, whether you should ship a fix tomorrow.
Cowork's built-in telemetry logs your skill as Skill: 3. Three invocations. Across 412 sessions for one client this month, you have a single number per skill — invocation count. Nothing about which versions ran, what they returned, whether the user accepted the answer or had to ask twice.
You shipped weekly-review four weeks ago. Across the first 38 sessions, users accepted the answer on the first turn. Across the next 9, they re-asked, rephrased, switched tools. Something started failing on session 39. Nobody noticed — the cost line stayed flat and no single session looked broken on its own.
Across the team's traffic this month, “turn this Linear ticket into a release-notes entry” came up fourteen times in eight different phrasings. Each one got a different ad-hoc answer; one user gave up. A skill is waiting to be written there. No telemetry surface — yours or anyone else's — will ever find it.
The instrument
Argus runs as a Claude Cowork plugin. It captures every session — prompts, assistant responses, every tool call, every follow-up — in plain text, stitched back into the conversation the user actually had. The qualitative layer that makes everything else possible.
A skill that works ends the conversation. A skill that doesn't gets re-prompted, rephrased, abandoned. Argus captures the user's exact follow-ups so the Agent can see, at a glance across hundreds of sessions, which versions of which skill are landing on the first turn — and which aren't.
Captured · used in: first-turn acceptance, follow-up patterns
Skills should answer questions, not ask new ones. When a skill is under-specified, the assistant stalls — “could you clarify…”, “which one did you mean…” — and the user does the work the skill was meant to do. Argus captures the stalls so the Agent can show where they cluster.
Captured · used in: stall frequency, under-specified prompts
The MCP call succeeded. Status 200. But the payload was empty, or a 400-row dump, or a JSON that didn't match what the skill asked for. Argus captures the tool's plain-text output beside the assistant's response, so the Agent can flag the sessions where the skill kept going on bad input.
Captured · used in: tool-output mismatches, silent failures
The prompts your customisations don't yet cover. Same export, same lookup, same wrangle — captured verbatim, even when nothing answered them. The Agent reads across the unmet-prompts corpus and surfaces patterns ready to become the next skill.
Captured · used in: unmet-prompt clustering, skill candidates
The loop
Five moves, read bottom-up — raw work at the foundation, refined knowledge on top. Each layer rests on the one beneath it; the loop settles new and refined skills back into the next session.
Rate the work; an agent refines weak skills and drafts the ones your usage is asking for.
Replay grouped by skill; analyse every invocation across the org.
Redacted and tenant-isolated, then each session is rebuilt into a complete, structured record — the data model that makes the detail possible.
Plugin hooks and OpenTelemetry capture every prompt, tool call, reply and metric — at the source.
People run their everyday Cowork sessions — the foundation everything rests on.
The agent
The Argus Agent reads across thousands of sessions of the same skill, MCP, or agent — and tells you the next move. Available in the Argus web app. Coming as a Claude Cowork plugin you can invoke during a working session.
Every Cowork session captured and indexed. Filter by user, project, skill, or status. Annotate any turn. Diff version-by-version what a skill produced.
The qualitative spine
First-turn acceptance · follow-up rate · stall frequency · tool-output mismatches, per version, over time. The week something starts drifting, the chart bends before any single session looks broken.
Per skill · per version · per client
The Agent reads across a skill's failed and refined sessions and proposes concrete edits to the SKILL.md — sharper trigger, missing tool, an example that would have caught the failure. You approve the patch; the new version lands in the marketplace as a pull request.
Patch · review · merge
The same Agent clusters the unmet prompts across the workspace and drafts candidate skills — the recurring asks your team didn't realise were systematic. Less guesswork. More shipped.
From recurring asks to draft skills
The Argus Agent is itself a Claude Cowork plugin
It runs the same way every other skill on the platform runs. It captures itself. It reviews itself. It refines itself. The thing the consultant is shipping is running on the rails the consultant is shipping.
The workshop uses the workshop.
A sample exhibit
One real session from a forward-deployed engineer's portfolio. Names redacted. This is what the Agent reads.
Pull Q2 churn from HubSpot and Stripe, cross-reference with NPS scores from [redacted-customer] in Intercom, and write up the top three churn drivers in our internal weekly-review voice.
I'll pull the cancellation reasons from Stripe and the closed-lost notes from HubSpot in parallel, then join them against the NPS responses Intercom logged in the same window. Kicking off three Explore subagents — Stripe's rate-limited so it'll iterate.
Tokens
Cost breakdown
Annotations · 2
matt · 18m ago
Churn write-up is solid, but the missing HubSpot cohort should have been caught at the join step. Track for workflow review.Data & privacy
Argus captures the conversations your customisations run. We have to be careful with them. Four commitments we won't move on.
The capture plugin scrubs API keys, OAuth tokens, Bearer headers, and common password patterns at the source — before the envelope leaves the user's computer. Anthropic, OpenAI, Supabase, GitHub, AWS, Slack patterns are caught by default; you can add your own.
Built · plugin-side · pre-transit
Type /private in Cowork at any point and the plugin stops capturing that session — and deletes anything already shipped. The escape hatch is the user's, not the agency's. No support ticket, no admin approval.
Built · the /private command
Per-workspace patterns for emails, names, and custom regex run on every captured envelope before it's persisted. Reviewers see [redacted-customer], not the company name.
Coming · per-workspace rules
TLS to the ingestion worker, AES-256 at rest in the database, workspace-isolated by row-level security on every query. Argus never uses your captured sessions to train any model — ours, Anthropic's, or anyone else's.
Standing policy · enforced at the database
Audience
The same captured session is read three ways. Each room sees what it needs to and nothing it doesn't.
The forward-deployed engineer
You ship custom skills to several clients. You need to know which versions are working at which client, where you're about to get a support ticket, and which user prompts are pointing at the next thing to build.
Primary user
The internal IT lead
You're standardising your org's MCP servers, you've published your first internal skills, and you need to know — across 200 engineers — which patterns work and which don't, before the leadership review.
Secondary user
The client stakeholder
You want to know your team's Cowork install is being used, that the skills you commissioned are landing, and you'd like to see one well-organised summary instead of a Slack thread.
Read-only · scoped
Progress
Where Argus stands as of June 2026. Numbers update as the private beta rolls forward.
Pilot workspaces
4
Two agencies, one internal IT team, one solo consultant. Coverage of all three audience types.
Sessions captured
142K+
From the live plugin running across pilot teams.
Public opening
June 26
Stable plugin, MCP-friendly skill catalog, version-diff QA — that's the bar.
Start
Sign in, create your workspace, drop the plugin into Claude Cowork — five minutes from a cold tab to your first captured session. Free during alpha, no card needed.
Step 1
Magic-link auth. We send a one-time link, you click it, you're in. No password to remember, no signup form to fill.
Sign in to ArgusWhat happens next
We don't sell your data, we don't train models on it, and you can opt any session out at any time.