AgentConnect is an open-source platform that lets teams and multiple AI agents collaborate in shared conversations and work processes across services such as Slack, Telegram, Discord, GitHub, GitLab, and Linear. Teams use it to assign agents roles, have agents call one another, and start work from messages, issues, pull requests, webhooks, or schedules.
Borrowing it
Nothing to install: this file belongs to agentconnect-md/agentconnect. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/agentconnect-md/agentconnect/main/.claude/skills/update-model-pricing/SKILL.mdgit clone --depth 1 https://github.com/agentconnect-md/agentconnectWrote 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.
[](https://agentmods.dev/skills/agentconnect-md/agentconnect/update-model-pricing)<a href="https://agentmods.dev/skills/agentconnect-md/agentconnect/update-model-pricing"><img src="https://agentmods.dev/badge/skills/agentconnect-md/agentconnect/update-model-pricing/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.
<a href="https://agentmods.dev/skills/agentconnect-md/agentconnect/update-model-pricing"><img src="https://agentmods.dev/badge/skills/agentconnect-md/agentconnect/update-model-pricing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.00699 |
| Opus 5.5 | $0.00032 | $0.00280 |
| Sonnet 5.5 | $0.00016 | $0.00140 |
| Haiku 4.5 | $0.00008 | $0.00070 |
Grade A, and why
update-model-pricing 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Update Model Pricing
Keep the daemon's offline cost fallback aligned with current public OpenAI Standard API pricing and the codex-acp version selected by AgentConnect's runtime registry or an explicit runtime override.
Workflow
- Read
packages/daemon/src/usage/openai-public-pricing.ts, its focused test, andpackages/daemon/src/runtimes/registry.ts. Resolve the effective codex-acp package/version from the current ACP registry entry or the deployment's explicit runtime command/args; it is not pinned inpnpm-lock.yaml. - Read references/pricing-sources.md and fetch the current official sources. Do not rely on remembered prices or third-party tables.
- Re-check the resolved codex-acp tag's
TokenCountmapping and compare it with upstream main before changing the formula. Confirm whether ACP input, cache-read, cache-write, output, and thought fields are disjoint and whether PromptResponse usage is per-turn. - Update the manifest with exact published model IDs, prices, dated snapshots, thresholds, and the verification date. Cover text/reasoning models that codex-acp advertises or AgentConnect explicitly supports; do not broaden the manifest to unrelated OpenAI products. Keep unknown models unsupported; never infer a price by prefix or strip an unlisted date suffix.
- Update tests in the same patch. Cover every alias, the exact long-context boundary, cache behavior, unknown models, malformed usage, and reasoning non-duplication.
- Run the focused daemon tests, daemon typecheck, and formatting check. Review the final diff for unrelated product or telemetry changes.
Repository Rules
- Price Standard API tokens in USD per one million tokens. Do not branch on ChatGPT subscription versus API-key authentication.
- Prefer an ACP-provided cost for a turn. Run fallback calculation only when that turn reports no cost.
- Keep cost display unchanged. Do not add estimated labels, approximation glyphs, or CP/Web schema fields unless explicitly requested.
- Calculate each Codex turn with the model selected for that session at turn start; do not reprice a whole session using its final model.
- Treat output tokens as already including reasoning tokens. Never add thought tokens a second time.
- Apply a long-context tier only when the public table publishes one and request input is strictly above its documented threshold.
- Keep runtime pricing offline and deterministic. Never fetch prices from the daemon at runtime.
- Preserve historical stored amounts; a price refresh affects only future fallback turns.
What ships with it
2 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.
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.
- 2mo ago First seen · 41 lines · 79 tokens per session scan A ea290671622a
update-model-pricing is a skill published in the GitHub repository agentconnect-md/agentconnect (1,520 stars, last pushed today), licensed Apache-2.0. It adds 79 tokens to every session and 699 once invoked, about $0.0003 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.
update-model-pricing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| update-model-pricingagentconnect-md/agentconnect | Skill | 1.5k | today | Apache-2.0 | A | 79 | Claude Code, Codex |
| tushareHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 79 | Claude Code, Codex |
| correlation-analysisHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 57 | Claude Code, Codex |
| social-media-intelligenceHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 28 | Claude Code, Codex |
| vibe-tradingHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 172 | Claude Code, Codex |
| ashare-pre-st-filterHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 89 | Claude Code, Codex |
| credit-analysisHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 36 | Claude Code, Codex |