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chatgpt-web-bridge

通过 chatgpt-web 的 MCP 或 REST 桥,把本地 agent 接入已登录的 ChatGPT Web。 适用于“推进/继续网页端会话”“让网页端设计、本地执行”“协作/对等推进”,以及只读拉取网页端会话/项目资料和 conversation_id 续接。 桥只传递文本;网页端没有本地 shell、文件系统或其他本地工具。

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/chatgpt-web-bridge/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a dense, highly operational playbook with genuinely non-obvious discipline (result-first calls, receipt semantics, lifecycle separation) and concrete tool/field-level guidance. Its weaknesses are verbosity from over-packed run-on paragraphs and a monolithic single-file structure that inlines material better kept in one-level-deep references.

Suggestions

Split deep-detail material into one-level-deep reference files (e.g., references/channels.md for the stdio/daemon/REST lifecycle and runtime fingerprint verification, references/read-mode.md for the D-mode out_file/partial/operation_id edge cases) and keep SKILL.md as a shorter overview with clearly signaled links.

Break the multi-rule run-on paragraphs (notably the send_seq/WinError 10054/session_key bullet and the restart-authorization paragraph) into short discrete rules so each constraint is independently scannable.

Add one complete worked call sequence per channel (e.g., a minimal MCP advance-turn and a REST request with explicit conversation_id) so the actionability guidance is copy-paste ready for each lifecycle model.

DimensionReasoningScore

Conciseness

There is essentially no conceptual padding — every paragraph carries non-obvious operational discipline (receipts, delivery stages, partial reads, runtime fingerprints) rather than things Claude already knows. However, several sections pack many distinct rules into single overloaded run-on sentences (e.g., the D-mode bullets on send_seq/WinError 10054/session_key, and the lifecycle paragraphs on fingerprints and restart authorization), so the content could be noticeably tightened.

3 / 5

Actionability

Concrete guidance throughout: exact tool names (chat_completion, wait_reply, get_conversation, list_projects), exact field names (delivery_stage, out_file, partial, retry_after, readiness.reason), a worked call example (chat_completion(message="继续", conversation_id=C)), a correction-message template, and the peer envelope. Minor gaps: no complete end-to-end call sequence for the REST channel.

4 / 5

Workflow Clarity

Multi-step processes are clearly sequenced: a mode-selection table up front, per-mode turn shapes, explicit termination conditions for every mode, an 8-step numbered result-first calling discipline, and validation checkpoints (consume the full return value before the next call, verify runtime_info fingerprints before restart, user gates on destructive actions). It falls short of 5 because some checkpoints are buried in dense prose rather than surfaced as explicit validate-then-proceed steps.

4 / 5

Progressive Disclosure

The skill is a single well-sectioned 155-line SKILL.md with no bundle files at all. Section headers are clear, but content that clearly belongs in separate reference files — the channel/lifecycle and fingerprint-verification detail, and the D-mode edge-case bullets (out_file exports, operation_id recovery, daemon/session rebinding) — is inlined, matching the 'content that should be separate is inline' anchor.

3 / 5

Total

14

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it concisely states what the bridge does, gives explicit quoted trigger scenarios, and delimits scope (text-only, no local tools on the web side). Its only weakness is that capability descriptions stay at a moderate level of granularity without naming the concrete tools involved.

DimensionReasoningScore

Specificity

The description lists several concrete actions — bridging a local agent into logged-in ChatGPT Web via MCP or REST, advancing/continuing web sessions, read-only pulling of conversations/projects, and conversation_id continuation — plus a boundary statement ('桥只传递文本;网页端没有本地 shell、文件系统或其他本地工具'). It falls just short of the 5 anchor because the actions are stated at a capability level without naming any specific tools or operations.

4 / 5

Completeness

It explicitly answers both questions: 'what' is '把本地 agent 接入已登录的 ChatGPT Web… 桥只传递文本' and 'when' is the explicit '适用于…' clause listing concrete trigger scenarios with quoted phrases. The missing-'Use when' cap does not apply since equivalent explicit trigger guidance is present.

5 / 5

Trigger Term Quality

It quotes natural user-intent phrases users would actually say ('推进/继续网页端会话', '协作/对等推进', '只读拉取', 'conversation_id 续接'), giving good keyword coverage. A few natural synonyms users might use (e.g., 'ChatGPT 网页', '接管会话', '拉取历史') are missing, so it fits the 'good coverage, a few natural terms missing' anchor rather than the comprehensive one.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (a chatgpt-web MCP/REST bridge for a logged-in web session) with distinct trigger phrases tied to that exact scenario, so conflict with other skills is minimal.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

ooooooooooooooooooop/agent-tools

Path

skills/chatgpt-web-bridge/SKILL.md

Reviewed

Table of Contents

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