Agent Skillsneilsonnn/image-blaster › image-blast-wildcard

image-blast-wildcard

GitHub

用于发现并执行任意 FAL API 图像生成模型。通过搜索 API 推荐候选模型,经用户确认后构建输入参数并调用脚本运行请求,支持本地文件处理及多模式执行,作为通用图片生成的兜底技能。

.claude/skills/image-blast-wildcard/SKILL.md neilsonnn/image-blaster

Trigger Scenarios

需要调用未预定义的 FAL 图像生成模型 通用图片生成需求且无特定专用技能可用

Install

npx skills add neilsonnn/image-blaster --skill image-blast-wildcard -g -y
More Options

Non-standard path

npx skills add https://github.com/neilsonnn/image-blaster/tree/main/.claude/skills/image-blast-wildcard -g -y

Use without installing

npx skills use neilsonnn/image-blaster@image-blast-wildcard

指定 Agent (Claude Code)

npx skills add neilsonnn/image-blaster --skill image-blast-wildcard -a claude-code -g -y

安装 repo 全部 skill

npx skills add neilsonnn/image-blaster --all -g -y

预览 repo 内 skill

npx skills add neilsonnn/image-blaster --list

SKILL.md

Frontmatter
{
    "name": "image-blast-wildcard",
    "description": "Discover and run any FAL API model or operation the user requests. Use this as a generic FAL escape hatch when the user wants to generate something that does not fit a narrower Image Blast skill.",
    "allowed-tools": "Read Write Glob WebFetch WebSearch Bash(ls *) Bash(node .claude\/scripts\/project\/ensure-local-assets.mjs *) Bash(node .claude\/scripts\/fal\/run-fal.mjs *)",
    "argument-hint": [
        "FAL model\/endpoint or natural request"
    ]
}

Resolve one arbitrary FAL API operation from $ARGUMENTS, confirm it with the user, then run it only after confirmation.

Instructions

  • There are two modes:
    • Discovery mode: normal user requests. Do not run a paid FAL request, call run-fal.mjs, or launch the background image-blast-wildcard agent until the user confirms the exact endpoint.
    • Execution mode: prompts that start with CONFIRMED_FAL_ENDPOINT: <endpoint>. Do not ask for model confirmation again; validate inputs and run exactly one request.
  • Discover candidate models with the FAL Platform Model Search API, not the Explore page:
    • https://api.fal.ai/v1/models?q=<query>&status=active&limit=5
    • https://api.fal.ai/v1/models?category=<category>&status=active&limit=5
    • https://api.fal.ai/v1/models?endpoint_id=<endpoint>&expand=openapi-3.0
  • Use https://fal.ai/docs/llms.txt and the model API docs only as fallback context when the model search response is insufficient.
  • Present the best candidate endpoint(s), category, description, and any relevant schema notes. Ask the user to confirm one exact model endpoint before execution, naming it directly, such as confirm fal-ai/flux/dev.
  • After confirmation in discovery mode, fetch the confirmed endpoint with expand=openapi-3.0, build schema-shaped JSON from the user's literal inputs, resolve the output location from the user's request or surrounding project context, and launch Agent(image-blast-wildcard) with a prompt that starts with CONFIRMED_FAL_ENDPOINT: <endpoint>.
  • Build the request JSON from the schema and the user's literal inputs. Use schema defaults for optional fields. Ask only if a required field cannot be inferred, a referenced local file is missing, or FAL_KEY is unavailable.
  • Use ls -a before reading generated state. Do not use a dedicated wildcard directory by default; choose the output directory contextually from the user's request, the active Image Blast project/world, an input file's surrounding generated-output directory, or another clear local workflow context. If no output location can be inferred, ask before execution.
  • For local file inputs, pass them with --file <schema_key>=<path> so the helper converts them to model input URLs. For nested keys use dot paths, such as image_urls.0.

The confirmed background agent should run:

node .claude/scripts/fal/run-fal.mjs \
  --endpoint "<fal endpoint, such as fal-ai/flux/dev>" \
  --input-json '<schema-shaped JSON input>' \
  --output-dir "<output directory>" \
  --output-slug "<short output slug>" \
  --user-prompt "<literal user request>"

Use --mode run only when the FAL API page requires a direct fal.run call instead of the queue API. The default queue mode persists request metadata before polling and downloads any returned file URLs.

If request metadata records provider URLs but local files are missing, fill them from the matching hidden request JSON:

node .claude/scripts/project/ensure-local-assets.mjs --from "<request-json-path>"

Final response before confirmation: ask for confirmation of the exact endpoint. Final response after execution: report the endpoint, input summary, output directory, downloaded output files, request metadata, and any raw result fields that were not downloadable.

Version History

  • 4acb43b Current 2026-07-24 11:45

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