English lecture · source-traced

OpenAI4S source-analysis file · verification report

**Object of verification**: `项目分析/OpenAI4S-源码分析.md` (v1, baseline commit `85e9fa0`) + checked against the real source `参考项目/OpenAI4S` **Method**: 6 parallel Explore agents, clustered by Part, file-by-file (Part I–II / III / IV / V / VI–VII + independent line-number spot-checks); each claim judged VERIFIED / WRONG / PARTIAL / UNSUPPORTED **Verification date**: 2026-08-04 **Conclusion first**: this is the **highest-qua

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Object of verification: 项目分析/OpenAI4S-源码分析.md (v1, baseline commit 85e9fa0) + checked against the real source 参考项目/OpenAI4S Method: 6 parallel Explore agents, clustered by Part, file-by-file (Part I–II / III / IV / V / VI–VII + independent line-number spot-checks); each claim judged VERIFIED / WRONG / PARTIAL / UNSUPPORTED Verification date: 2026-08-04 Conclusion first: this is the highest-quality analysis in the series—numeric claims all hit, line numbers with almost zero drift, the inference layer already labeled as inference. Problems concentrate in a single-digit count of factual deviations (1 WRONG + a dozen-odd PARTIAL), all already corrected in place.

Part 1

1. Overall scores

Dimension Score Notes
Line-number accuracy ★★★★★ Spot-check of 10 independent citations: 0 drift; actions.py:176-185, app.js:5574, POST /frames/{id}/message @ 9654, TOOL_TYPES @ 118-189, and others exact to the starting line
Numeric credibility ★★★★★ 255 .py / 114k LOC / 286 tests / 34 skills / 70 TOOL_TYPES / 0 core dependencies—all exact against source, no inflation or shrinkage
Mechanism description ★★★★☆ Dual-plane engine, three iron rules of route_action, finalize vs submit_output attribution, ledger-first, Store single connection—no misattribution (except 18.1 below)
Inference discipline ★★★★★ Ch. 19–20 uniformly use the four-part “claim → evidence → what is given up → taste,” and Ch. 20 is explicitly labeled “reverse-inferred,” not packaging speculation as fact
Completeness ★★★★☆ 22 chapters cover dual-plane / Host / Kernel / Tools / Provider / Web / Skills / Compute / Security / taste / comparison; a few domain-classification tables have omissions

Overall: among “AI-generated source analyses,” a rare high-water mark. What needs correction is detail, not the skeleton.

Part 2

2. Where the analysis was wrong (already corrected in place)

🔴 WRONG (1 place, must change)

18.1 Permission / approval-layer path misattributed - Original: security/permissions.py - Fact: the approval broker is top-level openai4s/permissions.py (771 lines, opencode-style allow/deny/ask gate, OPENAI4S_UNATTENDED_APPROVAL at :383). The same-named security/permissions.py (116 lines) only manages data-directory file permission bits (SQLite plaintext credentials default 0644, then tightened) and has nothing to do with approval. - Already changed: openai4s/permissions.py + storage/permissions.py, with a WRONG annotation added. - Likewise 23.1 reading-order line 13 was corrected together.

🟡 PARTIAL (the key few, already changed; the rest in the appendix batch table)

# Location Problem Fix
1 13.2 event-type table Listed cell/artifacts/permissions as WS event type—none of them are; real types are artifact_created/permission_resolved/kernel_status and the like; cell is a live-buffer scope value Table rewritten + WRONG annotation added
2 19.3 point 2 “dup2 / fd3·fd4” mixed two mechanisms: Python worker.py uses os.dup() anonymous high fds + dup2(2,1), no fd3/fd4 constants; fd3/fd4 are R-channel specific (r_kernel.py:12-13) Qualifying note added
3 17.1 Used remote-compute-ssh as a provider-shim example—it has only SKILL.md+README, no provider.py, a pure recipe Noted
4 2.2 Quoted "Never add hard third-party import" cited as CLAUDE.md:11; the real line is :90 Changed to :90
5 18.3 egress.py:9-10 docstring claims it “does not ship an OS-level sandbox,” which directly conflicts with and is stale relative to security/sandbox.py (the real Seatbelt/bwrap implementation); the original patched this for the author but still attributed it to egress.py Docstring marked stale
6 Choice 7 Façade list named 6 files; CLAUDE.md:98 actually lists 7, omitting sdk/host.py Added
7 14.1 / 23.1 / 20 Real path of webui/app.js is openai4s/server/webui/app.js; egress.py is top-level, not under security/ Unified
8 4.1 “State-machine body ~143 lines”—143 is the engine.py file line count; the class body (34-143) is 110 lines See appendix
9 12.2 gateway.py:6337-6447 _loop actually extends to ~6484 (closed 37 lines early) See appendix
10 10.1 TOOL_TYPES domain table omitted the “dynamic tools” family of 6 types + SearchCapabilitiesTool; a reader summing the table gets only 63 See appendix
Part 3

3. Evaluation of this analysis file (strengths)

  1. Rare numeric honesty. Most AI analyses inflate scale; this one’s 255/114k/286/34/70/0 all recompute, and “zero third-party dependencies” was confirmed by an AST scan of all-package imports (only 7 try/except guards), not by looking at pyproject and stopping.
  2. Line numbers are “re-checkable,” not decoration. Appendix-C-style numeric snapshots, the 23.2 symbol lookup table 15/15 hits, 14.1 lining up send()’s sub()→POST→202→admissionId timing line by line to app.js:5640-5676—this precision means the writer actually read the source, not an LLM hallucination.
  3. The inference layer has discipline. Ch. 20 “ten developer choices” is explicitly reverse-inferred; the layout separates “evidence” from “taste.” That avoids the common disease of packaging the author’s speculation as source fact.
  4. Product view is in place. 13.2’s wait:false + sub() first race, 14.3’s client-generated admissionId, 18.2’s approval-restart semantics—these “product-level details” are grabbed accurately, showing the analyst knows where an “agent workbench” breaks.
  5. Cross-project comparison is honest. 22.2 honest bounds fills many cells with “unknown / closed source,” and does not invent other-project details to make the table look complete.
Part 4

4. Improvement suggestions

A. Immediate (low cost, high return)

  1. Build a “line-number check footnote” mechanism: every analysis that emits file:line should attach a grep -n check-script dump at the end of the document (as the Codex analysis does: “all citations re-checked with grep”). This OpenAI4S pass is already close to that standard; recommend freezing it as a template.
  2. Inject WRONG/PARTIAL marks into the document: this pass already added ⚠️ 核查修正（2026-08-04） blocks in the body. Recommend every verified analysis use this format uniformly, so a reader can tell “original conclusion” from “post-hoc errata” at a glance.
  3. Patch the appendix batch table (below): 13 places of ±1-line drift and domain-table omissions—these come from copy-pasting a neighboring version; a batch edit is enough.

B. Structural

  1. Add an unfalsifiable disclaimer to “other-project comparison”: in Ch. 21’s cross-project table, OpenAI4S itself is listed as fully VERIFIED, but the other-project columns (Claude Code/OpenManus/Codex/Open Design) are cross-repo judgments this repository cannot falsify. Recommend a footnote on every comparison table: “other-project columns are public materials / author judgment, not falsifiable in this repository.”
  2. Give the dynamic-tool family its own section: among TOOL_TYPES’s 70 subclasses, “dynamic tools” (Define/List/Promote/ListVersions/Activate/Rollback) are first-class citizens and deserve their own 10.1 subsection, rather than being buried in the “files / web / science” domains.
  3. Write the egress–sandbox relation clearly: the stale docstring on egress.py will confuse readers. Recommend one sentence between 18.1 and 18.3: “egress is an application-layer domain fence; sandbox is OS-level process isolation; the two are orthogonal; egress’s docstring claim that it ‘does not ship an OS sandbox’ is an old formulation; take sandbox.py as authoritative.”

C. Longer term

  1. Sync multiple copies of the same source: this repository’s OpenAI4S-源码分析.md (root) and 项目分析/OpenAI4S-源码分析.md are two copies of one document; they were synced in this pass. Recommend establishing a single source of truth (prefer 项目分析/), leaving only a build entry at the repo root, so one edit is not missed in the other. The Codex analysis has the same dual-copy problem.
  2. Close the HTML delivery loop: this pass found that HTML had never been generated for the OpenAI4S and Codex analyses (markdown only). OpenAI4S-解析.html and 项目分析/openai-codex-源码分析.html have now been generated. Recommend putting “generate HTML” on each analysis’s delivery checklist.
Part 6

Addendum: the openai-codex analysis checked along the way (bonus from a misidentified target)

The user’s spoken "openai4s" was first taken as openai-codex, so an equivalent verification was run first on 项目分析/openai-codex-源码分析.md (commit bb1af23). That document’s line-number accuracy is equally high (spot-check 25 places, 0 drift), but 4 substantive errors were found and already corrected in place:

  1. 9.3 previous-model compact mechanism misattributed: 1032-1040 is capture_current_model_fallback_step_context (only decides retry-fallback context), not a compaction switch; the real trigger is maybe_run_previous_model_inline_compact (1057+), which does not check Codex backend/OpenAI provider. The original “do not play this on a third-party provider” is wrong.
  2. 15.4/15.7 Landlock/bwrap frame inverted: the Landlock FS ruleset source itself says “currently unused / legacy”; bubblewrap is the main Linux FS sandbox implementation. The original reversed their primary/secondary roles.
  3. 3.2 exec-server is not hidden: only an [EXPERIMENTAL] comment, no hide=true; it is a public subcommand.
  4. 22.1C debug_input invented: 0 hits in the whole tree; should be build_prompt_input / run_debug_prompt_input_command.

Also corrected 5 line-number/path deviations (16.2 with_cached_approval 71-117, 11.2 built_tools path added, 11.3 CodeMode directory ownership, 20.3 rollout path prefix, 22.3 turn.rs crate path added). 项目分析/openai-codex-源码分析.html has been generated.

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