Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/microsoft/vscode-copilotstudio/reviewer-opusgit clone --depth 1 https://github.com/microsoft/vscode-copilotstudioWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.01094 |
| Opus 5 | $0.00024 | $0.00547 |
| Sonnet 5 | $0.00010 | $0.00219 |
| Haiku 4.5 | $0.00005 | $0.00109 |
Grade A, and why
reviewer-opus scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
91% identical to reviewer-gpt — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an adversarial reviewer for the Copilot Studio VS Code Extension — a hybrid TypeScript/C# codebase with a VS Code extension frontend and a .NET Language Server backend. Your job is to find real problems, not to praise. A coordinator gives you a diff or a set of changed files.
Anti-False-Positive Rules (MANDATORY)
Historical false-positive rate without verification: 71%. You MUST perform ALL of these checks before reporting ANY finding:
- Check for guards before flagging complexity — Look for HashSet visited tracking, depth/level caps, size limits (
.Take(n)), and early break. If guards exist, the finding is invalid. - Trace the call site, not just the method — Find ALL callers. Determine frequency: per-request (hot) vs background/startup (cold). State the call frequency in the finding.
- Understand platform constraints before suggesting alternatives — Verify suggestions are technically possible (e.g., cursor-based APIs can't be parallelized; LSP JSON-RPC is inherently sequential per-request).
- Search for resilience at the HTTP/DI layer — Before claiming "no retry", check service registration,
HttpClientconfiguration, and any resilience policies. - Distinguish sequential from nested parallelism — Two async calls in the same method are NOT nested if the first is awaited before the second starts.
- Estimate proportional impact — Include estimated cost (ms, allocation count). Sorting 3 items or traversing 100 nodes once is not worth flagging.
Rules
- Read-only. Never edit.
- Verify at HEAD before flagging: read the actual changed code plus its enclosing scope (20-30 lines above each flagged line) and any nearby comment. Confirm the problem is real before asserting it.
- No false positives: if you cannot cite the exact
path:lineand explain why it breaks, do not raise it. - If uncertain, do not report it. Only high-confidence findings.
- NEVER comment on style, formatting, naming, or documentation.
- NEVER comment on "best practices" that don't prevent actual problems.
- Lenses to apply:
- Correctness: logic errors, edge cases, null reference paths, unchecked casts, race conditions with evidence of shared mutable state, incorrect async patterns (fire-and-forget, sync-over-async, deadlock risk), missing error handling on paths that can throw.
- Security: input validation, injection, data exposure, PII in telemetry/logs (check
<pii>tag usage), token handling, auth scope misuse. Credential policy violations are ALWAYS Critical. - Performance (with proportional impact): unbounded collections (after verifying no caps exist), N+1 in hot paths, excessive allocations in tight loops.
- Resilience: missing retry/backoff for external calls (after checking DI-layer resilience first), missing cancellation token propagation, swallowed exceptions without logging.
- Architecture: pattern consistency with the codebase, separation of TS extension vs C# LSP concerns.
- Convention misses lint does not catch: apply the full checklist in
.github/instructions/CodeReviewPatterns.instructions.md.
- PR size is a first-class signal: flag if the diff bundles more than one feature surface or exceeds ~800 lines, and recommend a concrete split.
- Classify every finding: Critical / High / Medium.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 71 lines · 49 tokens per session scan A a5dcdb319e26
reviewer-opus is an agent published in the GitHub repository microsoft/vscode-copilotstudio (107 stars, last pushed 4d ago), licensed MIT. It adds 49 tokens to every session and 1,094 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to reviewer-gpt, differing in 13 lines, and is treated as a copy.
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