AgentSight

Evidence shows a local-first system observability tool: eBPF probes need root, but docs state the monitored agent still runs as the normal user with only probes elevated, and there is a no-sudo fallback to snapshots and native session files (least_privilege=2). Data flow is documented in detail in the FAQ (local SQLite, ~/.agentsight/monitor, localhost web UI), earning high transparency (=3). However, captured content includes plaintext TLS LLM payloads, prompts, headers, and network targets; the docs only advise treating logs as sensitive, with no redaction/encryption or explicit user-confirmation flow, and the monitor can install a background service without a documented consent/undo path (user_confirmation=1, sensitive_data_handling=2, rollback=1). CI uses lockfiles and vendoring, but no audit/vulnerability scanning is shown (=1). Optional OTLP export is an explicit opt-in feature (=2). MIT license, eunomia-bpf attribution, and arXiv paper give clear sourcing (=2). Deductions: sensitive-data protection stays at the advisory level; no confirmation/rollback detail.

README, CI, and tests are mutually consistent: command examples (top/record/report/vis), field names, and test assertions align with one coherent event model (self_consistency=3). Dependencies (cargo/crates.io, npm, Chromium/FFmpeg) are addressed in docs and CI but carry external availability risk, e.g., GIF export needs local Chromium (=2). The FAQ provides troubleshooting guidance and tests use WARN/SKIP soft failure for kernel variance (failure_messages=2). No contradictions found; deduction is that failure handling is FAQ-based rather than systematic error codes/recovery docs.

Clearly targets Claude Code, Codex, Gemini CLI, OpenCode, and arbitrary commands, distinguishing the eBPF path from the agent-native session path (audience_and_scenarios=3). Capability boundaries are unusually honest: Cursor IDE not traceable via eBPF, statically linked SSL capture limits, kernel 4.1+/5.0+ requirements are all stated (capability_boundaries=3). Auto-discovery of binaries and SSL libraries lowers the barrier, but precision depends on explicit -p/--session selectors; default modes capture broadly (=2). Linux/macOS/partial Windows plus Docker are covered with environment-specific notes (environment_fit=3).

Documentation is well structured: Quick Start, Usage, FAQ, Contributing, License with a complete docs/ index (information_architecture=3). Installation covers cargo, Homebrew, binaries, Docker, and source builds with platform differences (install_notes=3). Examples are abundant and consistent with the command table; the FAQ directly addresses permissions, performance, data location, and failure triage (examples_and_faq=3). Known limitations (Cursor, static SSL, unpublished Windows assets) are stated (known_limitations=3). The MIT LICENSE file matches the badge (license=3). Naming is mostly stable (agentsight/agentpprof) though the unsuffixed asset is a vague 'compatibility alias' (=2). Versions are semver-managed by CI, but the release snapshot force-pushes master and changelogs rely on generated notes (versioning_changelog=2). Maintainer is the eunomia-bpf org with a clear release process, but publisher identity is unverified (maintenance_responsibility=2).

Output usability is strong: live top view, web dashboard, report JSON/SQLite queries, standards-based OTel export, and pprof-compatible flamegraphs (output_usability=3). Relative to application-level tools like LangSmith/Langfuse, it fills the system-boundary gap with zero-SDK adoption; the marginal value argument is explicit and differentiated (marginal_value=3). The <3% CPU overhead claim cites a paper but cannot be reproduced in static review, and the eBPF+root+privileged-Docker operational cost is nontrivial for ordinary users (cost_benefit=2).

Most claims trace to in-repo material: the <3% overhead figure points to the arXiv paper and DOI; install/build claims point to docs files; CI steps map to repo paths (claim_traceability=2). README, CI workflows, and bpf tests corroborate the event model and command behavior across three sources (cross_source_corroboration=2). Facts and inference are mostly separated, but promotional framing ('The Future of AI Observability') and the performance number are not distinguished by evidence strength in-text (fact_inference_separation=2). Deduction: no in-repo benchmark data backs the performance claim, and it cannot be verified statically.