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claude-to-deerflow

Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

90%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, fully executable API guide: copy-paste curl commands for every operation, exact env-var resolution, SSE event semantics, context modes, and a properly referenced helper script. Its only weaknesses are moderate — no explicit error-recovery/feedback loops in the main workflow, and an unreferenced bundle script (scripts/status.sh) that a reader of SKILL.md alone would never find.

Suggestions

Add a short mention of scripts/status.sh in the body (e.g., a Status section: `bash scripts/status.sh [models|skills|agents|threads|memory|thread <id>]`) so both bundle scripts are discoverable from SKILL.md.

Strengthen the primary message workflow with an explicit validation checkpoint between thread creation and streaming — verify thread_id was returned before POSTing the run, and retry or surface the raw response if parsing fails.

Add a brief fix-and-retry path in Error Handling for a run that fails mid-stream (e.g., re-issue the run on the same thread_id), turning the current one-way error notes into a feedback loop.

DimensionReasoningScore

Conciseness

Every section is operational detail Claude cannot infer: env-var resolution, exact curl commands with headers and JSON bodies, SSE event types, context-mode flag combinations, and parsing rules. There is no explanation of concepts Claude already knows and no padded prose — matching "Lean and efficient; assumes Claude's competence; every token earns its place". It is not a 4 because no section could be trimmed without losing executable information.

5 / 5

Actionability

All twelve operations are given as complete, copy-paste-ready curl commands with concrete URLs, headers, and request bodies (e.g., the full streaming POST body including assistant_id, stream_mode, and context flags), plus expected response shapes and a helper script invocation. This matches "Fully executable; copy-paste ready code or commands; specific examples cover the common cases"; the primary message flow needs only the user's text and thread_id substituted.

5 / 5

Workflow Clarity

The primary workflow is clearly sequenced (health check → create thread → stream run) with an explicit pre-flight checkpoint ("Read these env vars before making any request", health check section) and a dedicated Error Handling section covering unreachable services and stream error events. It falls short of the 5 anchor because there are no explicit feedback loops — e.g., no guidance to verify the thread was created before streaming, nor a fix-and-retry path if a run fails mid-stream — while exceeding the 3 anchor whose checkpoints are only implicit.

4 / 5

Progressive Disclosure

Structure is good: clear sectioned overview, numbered operations, and a well-signaled reference to the bundle script ("See `scripts/chat.sh` for the implementation" with a summary of what it does). It is not a 5 because the second bundle script, `scripts/status.sh`, exists but is never mentioned anywhere in the body, leaving it undiscoverable; it is above a 3 because the inline content is appropriate for the skill's size and the one reference made is clearly signaled one level deep.

4 / 5

Total

18

/

20

Passed

Description

100%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.

The description is exemplary: it states the concrete capability set in third person, provides an explicit "Use this skill when..." trigger clause with multiple natural scenarios, includes the platform name and its spelling variant, and stays tightly scoped to DeerFlow with no fluff or over-claiming. All four dimensions sit at the top anchor.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks" — comprehensively covering the skill's operations with no vague filler. This matches the anchor "Lists multiple specific concrete actions; comprehensive coverage"; a 4 would require noticeable coverage gaps, which are absent (thread history/listing are reasonably subsumed under thread management).

5 / 5

Completeness

It explicitly answers "what" ("Interact with DeerFlow AI agent platform via its HTTP API" plus the enumerated capabilities) and "when" with a concrete "Use this skill when the user wants to..." clause listing trigger scenarios, and closes with additional trigger conditions. This directly matches the anchor "Clearly and explicitly answers both what AND when with concrete trigger phrases".

5 / 5

Trigger Term Quality

Natural triggers include the platform name and its variant ("the user mentions deerflow, deer flow") plus natural task phrasings users would actually say ("send messages or questions", "check DeerFlow status or health", "upload files", "run a deep research task"). For a named-platform skill this is comprehensive coverage including synonyms; it is not a 4 because no commonly used natural phrasing for invoking this platform is missing.

5 / 5

Distinctiveness Conflict Risk

The skill occupies a clear niche — a specific named platform (DeerFlow) — and every trigger is scoped to it ("to DeerFlow", "in DeerFlow", "DeerFlow can handle"), giving minimal overlap risk with other skills. A 4 would require minor overlap risk with closely related skills, which the explicit platform scoping avoids.

5 / 5

Total

20

/

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
bytedance/deer-flow
Reviewed

Table of Contents

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