video-provider-capabilities

video-provider-capabilities is a skill for Claude Code, Codex from manishiitg/coding-agent-loop. It costs 94 tokens per session (1,712 once invoked), scanned A, original, MIT.

A planning workflow that checks an AI video model’s current official API rules before a paid request. An API is the interface software uses to send requests to a service.

In plain words
What is it for?
It helps prepare requests for Kling, Seedance, Veo, and other models, including image, video, and audio references, first or last frames, retries, cost planning, and review.
Why use it?
Video models can differ in accepted inputs, request formats, continuity options, and pricing. Checking those rules helps prevent failed or unsuitable paid calls.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps prepare requests for Kling, Seedance, Veo, and other models, including image, video, and audio references, first or last frames, retries, cost planning, and review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/manishiitg/coding-agent-loop/video-provider-capabilities
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add manishiitg/coding-agent-loop --skill video-provider-capabilities
Clone the repo
git clone --depth 1 https://github.com/manishiitg/coding-agent-loop

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for video-provider-capabilities

README.md
[![agentmods](https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/video-provider-capabilities/github.svg)](https://agentmods.dev/skills/manishiitg/coding-agent-loop/video-provider-capabilities)
Your own site
<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/video-provider-capabilities"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/video-provider-capabilities/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for video-provider-capabilities

Your own site · 80×15
<a href="https://agentmods.dev/skills/manishiitg/coding-agent-loop/video-provider-capabilities"><img src="https://agentmods.dev/badge/skills/manishiitg/coding-agent-loop/video-provider-capabilities.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,712 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.01712
Opus 5.5 $0.00038 $0.00685
Sonnet 5.5 $0.00019 $0.00342
Haiku 4.5 $0.00009 $0.00171

Measured 1mo ago against content hash 9ffc1066f4a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

video-provider-capabilities scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent_go/internal/videoproduct/skills/video-provider-capabilities/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resolve provider capabilities before generation

Do not create a paid video request from a generic template or model-family memory. Before the first video call for a production, read the selected endpoint's current official API reference. For fal-hosted models use that exact endpoint's fal API page; for direct Google models use the current Google Gemini/Veo documentation. A model list discovers candidates; the endpoint schema controls the request. Models and higher-level workflows are different contracts. Do not infer one from the other.

Read these bundled references when their phase begins:

  • references/capability-record.md before resolving or refreshing a model.
  • references/continuity-planning.md before writing the shot list or request.
  • references/execution-review.md before spending, retrying, assembling, or presenting outputs.
  • video-model-selection/references/cost-guidance.md when comparing models or giving a user a costed choice.

Required artifacts

Write the following under the production folder in direct chat, or inside the current workflow-stage folder:

  • capabilities/<provider>-<model-slug>.json: the live endpoint contract.
  • continuity-plan.json: scene boundaries, reference lineage, seams, and the reason for every independent generation.
  • generation-ledger.json: cost estimate, exact submitted request, provider adjustments, job state, output, validation, presentation, and review.

These are required inputs and evidence for every paid video request. The capability record begins with:

{
  "schema_version": 2,
  "provider": "fal-ai or google-ai",
  "model_id": "exact resolved model id",
  "execution_mode": "queue or realtime",
  "checked_at": "RFC3339 timestamp",
  "official_docs": ["official API URL"],
  "input_contract": {
    "required": [],
    "optional": [],
    "media_roles": {"start_frame": {"min": 0, "max": 0}, "end_frame": {"min": 0, "max": 0}, "image_references": {"min": 0, "max": 0}, "video_references": {"min": 0, "max": 0}, "audio_references": {"min": 0, "max": 0}},
    "duration_seconds": {"min": 0, "max": 0},
    "multi_shot": {"supported": false, "field": "", "shape": {}},
    "extension": {"supported": false, "input_role": ""},
    "seed": {"supported": false, "field": ""},
    "native_audio": {"supported": false, "field": "", "values": []},
    "aspect_ratios": [],
    "resolutions": [],
    "mutually_exclusive": [],
    "output_contract": {}
  },
  "request_shape": {"exact field names": "copied from the official schema"},
  "pricing": {"source": "", "checked_at": "", "currency": "", "unit": "", "unit_price": null, "base_estimate": null, "retry_reserve": null, "maximum_approved_cost": null, "estimate_available": false},
  "continuity_fit": {"strategy": "...", "why": "..."}
}

Read the full file on GitHub · 146 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · +1 lines 9ffc1066f4a5
  2. 1mo ago Changed · +9 lines 677f141d7617
  3. 2mo ago First seen · 136 lines · 94 tokens per session scan A 2bef266ef97f

Subscribe to this mod's changes

video-provider-capabilities is a skill published in the GitHub repository manishiitg/coding-agent-loop (13 stars, last pushed 1mo ago), licensed MIT. It adds 94 tokens to every session and 1,712 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

doubt-driven-review

In-flight adversarial check on a non-trivial decision BEFORE it stands — distinct from post-hoc review of a finished diff. Use on "stress-test this decision", "are we sure about this", "verify before commit", "poke holes in this", when working in unfamiliar code, or before an irreversible step (migration, prod deploy…

BlackBeltTechnology/pi-agent-dashboard · 90 tokens

autofix

Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.

BlackBeltTechnology/pi-agent-dashboard · 30 tokens

code-review

AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security). Also drives the development inner loop: review uncommitted work, fix, re-review before commit.

BlackBeltTechnology/pi-agent-dashboard · 61 tokens

code-quality

Drive static-analysis code quality in pi-agent-dashboard with Biome (analyze → fix → test), in changed-files or whole-repo mode. Use when asked to "improve code quality", "lint and fix", "clean up warnings", "fix Biome issues", "run static analysis", or when setting a code-quality goal. Skip for one-line edits.

BlackBeltTechnology/pi-agent-dashboard · 77 tokens

fiber-rest-api

Use when adding or changing a Go HTTP endpoint — Fiber v2 or v3 (detect which), thin handlers, central error mapping, boundary validation; the same rules apply to net/http, chi, echo or gin.

makifbaysal/tasktrooper · 47 tokens

zerolog-observability

Use when adding logging to Go code - the repository's logger with structured fields, request-scoped correlation, correct levels, no secrets or double-logging.

makifbaysal/tasktrooper · 36 tokens