BD echoflow-image-gen
通过清云 EchoFlow API 生成和编辑图片（基于 Nano Banana Pro / Gemini 3 Pro Image）。 支持图片生成、单图编辑、多图合成（最多14张）、多种分辨率（1K/2K/4K）。 触发词：图像生成、图片生成、AI绘画、生成美女、生成图片、Nano Banana Pro、Gemini 图片生成。 English: Generate or edit images via EchoFlow API using Nano Banana Pro (Gemini 3 Pro Image). Supports image generation, editing, and multi-image composition (up to 14 images) with resolutions 1K/2K/4K.
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
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high Dangerous commands
cmd-pipe-to-shellSKILL.md:47Downloads and executes remote code from an unrecognised host (pipe to shell)# Linux (curl | sh — 检查脚本后再运行 / Inspect script before running)
Medium and low: 1
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medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:48Pipe-to-shell installer from a well-known host (still executes remote code)curl -LsSf https://astral.sh/uv/install.sh | sh
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 41/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (echoflow-image-gen) differs from the folder (echoflow-banana)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 8 steps
- 100Execution cost. Instruction body is 935 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 369: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.