Agent skill

Add Model

by simstudioai in simstudioai/sim

Add a new LLM model to apps/sim/providers/models.ts with specs verified against the provider's live API docs (no hallucination)

Apache-2.0Auto-check passedDevelopment

Install Add Model

skills CLI
$ npx skills add simstudioai/sim --skill add-model -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install simstudioai/sim add-model --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/simstudioai/sim.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/add-model .claude/skills/add-model && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
add-model
GitHub stars
30k
Token cost
~3.9k tokens
SKILL.md length
1,603 words
Files
2
Skills in repo
40
Repo updated
First seen
Licence
Apache-2.0

At a glance

Add a new LLM model to apps/sim/providers/models.ts with specs verified against the provider's live API docs (no hallucination)

  • Works in 6 steps: Live source-of-truth lookup → Consumption Matrix (which provider… → Match the provider's existing entry… → …
  • Tasks that involve Technical documentation
  • SKILL.md covers Hard rules (do not skip), Your Task, Step 1: Live source-of-truth… and Step 2: Consumption Matrix…, plus 5 more sections
  • Calls bun and rg; reaches docs.x.ai and openrouter.ai

What it does

Add Model is an agent skill from simstudioai/sim. Add a new LLM model to apps/sim/providers/models.ts with specs verified against the provider's live API docs (no hallucination)

Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Development, covering Technical documentation. It works with OpenAI. The repository describes itself as: Sim is the collaborative workspace to build, deploy, and monitor AI agents and workflows. Used by 100,000+ builders. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Technical documentation

Example prompts

  • “/add-model”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Live source-of-truth lookup
  2. Consumption Matrix (which provider honors which capability)
  3. Match the provider's existing entry pattern
  4. Repo-side touchpoints beyond the entry
  5. Write, lint
  6. Verification report (mandatory format)

What it can do on your machine

Read from SKILL.md and the folder at commit 546d4e7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • bun
    • rg

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • docs.x.ai
    • openrouter.ai
    • cloudprice.net

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Add Model loads about 3.9k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 1,603 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from simstudioai/sim at commit 546d4e7, republished under its Apache-2.0 licence (© simstudioai). 1,603 words, ~3,924 tokens.

Download SKILL.mdSave it as .claude/skills/add-model/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
add-model
description
Add a new LLM model to apps/sim/providers/models.ts with specs verified against the provider's live API docs (no hallucination)
argument-hint
<provider> <model-id> [docs-url]

Add Model Skill

You add a new model entry to apps/sim/providers/models.ts. Every numeric and capability claim MUST be derived from a live web fetch of the provider's official docs in this session. Marketing emails, training data, and your prior knowledge are not sources of truth — they routinely hallucinate pricing, context windows, and capability lists.

Hard rules (do not skip)

  1. Live-fetch or refuse. Before writing the entry, you must successfully WebFetch the provider's official models/pricing page in this session. If you cannot reach an authoritative source for any field, mark the field as UNVERIFIED in your report and ask the user before guessing. Never fill in pricing or capabilities from memory.
  2. Two-source rule for pricing. Cross-check input/output/cached pricing against at least one secondary source (OpenRouter, Artificial Analysis, CloudPrice, mem0, intuitionlabs). If sources disagree, the provider's own docs win — but flag the disagreement.
  3. Read the code before setting capability flags. Capability flags are dead unless the provider's implementation under apps/sim/providers/{provider}/ actually consumes them (see Consumption Matrix below). Setting a flag the provider ignores is a silent bug.
  4. Cite every fact. Your final report must list the URL each value came from. No URL → not verified.

Your Task

  1. Identify provider and model id from user args
  2. Live-fetch official docs + pricing page + capability/parameter pages + at least one secondary source
  3. Apply the Consumption Matrix to know which capability flags are real
  4. Read 2-3 sibling entries in models.ts and match their pattern exactly
  5. Check the repo-side touchpoints that are NOT data-driven (hosted-key billing, tests, provider code)
  6. Insert the entry, run bun run lint, print the verification report

Step 1: Live source-of-truth lookup

In priority order — fetch all that exist for the provider:

ProviderModels indexPricingReasoning/parameter caveats
OpenAIplatform.openai.com/docs/modelsopenai.com/api/pricingplatform.openai.com/docs/guides/reasoning
Anthropicplatform.claude.com/docs/en/about-claude/models/overviewclaude.com/pricing (API section)platform.claude.com/docs/en/build-with-claude/extended-thinking
Google (Gemini)ai.google.dev/gemini-api/docs/modelsai.google.dev/pricingai.google.dev/gemini-api/docs/thinking
xAIdocs.x.ai/developers/modelsdocs.x.ai/developers/models (per-model detail page)docs.x.ai/developers/model-capabilities/text/reasoning
Mistraldocs.mistral.ai/getting-started/models/models_overviewmistral.ai/pricingn/a
DeepSeekapi-docs.deepseek.com/quick_start/pricingsameapi-docs.deepseek.com/guides/reasoning_model
Groqconsole.groq.com/docs/modelsgroq.com/pricingn/a
Cerebrasinference-docs.cerebras.ai/modelscerebras.ai/pricingn/a

Secondary verification (use at least one): openrouter.ai/<provider>/<model>, artificialanalysis.ai/models/<model>, cloudprice.net/models/<provider>-<model>.

Use a precise WebFetch prompt: "Extract for {model_id}: exact model id string, context window in tokens, input price per 1M, cached input price per 1M, output price per 1M, max output tokens, supported reasoning effort levels, accepted parameters (temperature, top_p), release date. Do not fill in fields you cannot find."

Step 2: Consumption Matrix (which provider honors which capability)

CapabilityHonored byEffect if set elsewhere
temperatureAll providers (passed through if set)Safe but inert on always-reasoning models that reject it
toolUsageControlAll providers (provider-level default)Override per model only when that model differs
forcedToolUseanthropic/core.ts (anthropic, azure-anthropic, kie); defaults to toolUsageControlIgnored by every other provider; set false only on a model behind that core that cannot force tools
promptCachingCaller-placed cache breakpointsSet only where the vendor charges for opt-in caching (absent for OpenAI/Gemini implicit caching)
reasoningEffortopenai/core.ts, azure-openai, xai, deepseek, groq, zai, kimi, cerebras, meta, litellm (each index.ts)Not read by anthropic/gemini (they use thinking) or by mistral, openrouter, fireworks, vertex — re-grep before assuming
verbosityopenai/core.ts, azure-openai/index.ts onlyDead elsewhere
thinkinganthropic/core.ts, gemini/core.ts; deepseek, groq, zai, kimi (each index.ts) read the resolved thinkingLevelDead elsewhere
thinking.streamedDocs generator + getThinkingStreamVisibility (models.ts); anthropic/core.ts uses 'summary' to request display: 'summarized' on agent-events runsMandatory on Anthropic-family thinking models (agent-stream-docs:check fails without it); other families fall back to provider defaults
nativeStructuredOutputsanthropic/core.ts, bedrock/index.ts (via models.ts supportsNativeStructuredOutputs, which reads the flag)Dead elsewhere — fireworks/baseten/together/openrouter call their own provider-level supportsNativeStructuredOutputs that ignores the model flag (always on, always off, or OpenRouter API metadata)
maxOutputTokensRead by UI + executor for token estimationAlways meaningful — set if provider documents a cap
computerUseproviders/utils.ts (getComputerUseModels → computerUseModels routing)Set only on actual computer-use SKUs
deepResearchUI flag for routing to deep-research SKUsSet only on actual deep-research model IDs
memory: falseConversation persistence opt-outSet only when model genuinely cannot maintain history (e.g., deep-research)

Always re-grep before relying on this table — the codebase moves:

bash
rg "reasoningEffort|reasoning_effort" apps/sim/providers/<provider>/
rg "verbosity" apps/sim/providers/<provider>/
rg "request\.thinking|thinking:" apps/sim/providers/<provider>/
rg "supportsNativeStructuredOutputs|nativeStructuredOutputs" apps/sim/providers/<provider>/

Step 3: Match the provider's existing entry pattern

Open apps/sim/providers/models.ts, find PROVIDER_DEFINITIONS[<provider>].models, read 2-3 sibling entries. Match field order exactly:

ts
{
  id: '<exact-api-id>',
  pricing: {
    input: <number>,
    cachedInput: <number>,  // omit if provider doesn't offer caching
    output: <number>,
    updatedAt: '<today YYYY-MM-DD>',
  },
  capabilities: {
    // only flags the provider actually consumes — see matrix
  },
  contextWindow: <tokens>,
  releaseDate: '<YYYY-MM-DD>',
  recommended: true,        // only if new flagship; ask user before swapping
  speedOptimized: true,     // only on smallest/fastest tier
  deprecated: true,         // only on retired models
}
Reseller providers (azure-openai, azure-anthropic, vertex, bedrock, openrouter)

Model id MUST be prefixed: azure/, azure-anthropic/, vertex/, bedrock/, openrouter/. Pricing usually mirrors the upstream provider but verify on the reseller's own pricing page.

Insertion order

Within a family, newest first (as the existing entries are ordered). Across families, biggest/flagship at top of list.

  • At most one or two recommended: true per provider — the current flagship(s).
  • If you're adding a new flagship, ask the user before removing recommended from the previous flagship. Never silently flip it.
  • speedOptimized: true only on the smallest/fastest tier (nano, flash-lite, haiku class).
  • Use today's date for pricing.updatedAt; never copy a sibling's.
  • cachedInput is an explicit documented number — never derived from input (ratios vary by provider).

Step 4: Repo-side touchpoints beyond the entry

Adding the models.ts entry is most of the job because nearly every consumer is data-driven and picks the model up automatically: the ~40 query helpers in models.ts / providers/utils.ts, the public /models catalog (app/(landing)/models/utils.ts iterates PROVIDER_DEFINITIONS), the agent-block model dropdown, and copilot's isKnownModelId / suggestModelIdsForUnknownModel validation. The touchpoints below are the exceptions — they are not data-driven, so check each one.

Hosted = auto-billed, by provider

getHostedModels() in apps/sim/providers/models.ts returns the model IDs served with Sim's rotating hosted key and billed to the workspace via shouldBillModelUsage() (providers/utils.ts). It builds that list by expanding whole providers (getProviderModels('openai'), 'anthropic', 'google', and others) plus the static Fireworks catalog, so any model added under one of those providers is hosted automatically. Read the function before inserting — the provider set changes. Before you insert:

  • If the model should be BYOK-only / never-billed, do not add it under a provider that getHostedModels() expands — that silently enrolls it in hosted billing. After inserting, verify with getHostedModels().includes('<new-model-id>') (a one-line bun -e or the assertion in providers/utils.test.ts). Confirm hosting/billing intent with the user. (Ollama Cloud is a deliberately separate isReseller provider specifically to stay BYOK-only/never-billed.)
  • If the model should be hosted, the deployment must actually have a key for it — the provider's {PREFIX}_COUNT / {PREFIX}_1..N env vars must be set, or hosted runs fail at execution time.
  • State the hosted/billing status explicitly in the verification report.
Show full SKILL.md (579 more words)Show less
Tests with hardcoded model IDs

bun run lint does not run tests. A few tests assert specific model IDs and can break or need updating when you touch a hosted or flagship model:

  • apps/sim/providers/utils.test.ts — asserts membership of getHostedModels() / shouldBillModelUsage()
  • apps/sim/providers/index.test.ts and serializer tests — reference concrete model IDs
bash
rg "<new-model-id>|getHostedModels|shouldBillModelUsage" apps/sim/providers/*.test.ts

If anything matches, run the affected provider tests and update assertions as needed.

New API behavior is NOT data-driven

The Consumption Matrix (Step 2) tells you which capability flags are honored by existing provider code. But if the new model needs net-new request handling that the provider doesn't implement yet — a new beta header, a new thinking/reasoning encoding, a Responses-API quirk — you must edit apps/sim/providers/<provider>/core.ts / index.ts. Setting a flag whose behavior isn't implemented is a silent no-op. When you do edit provider code, reuse the shared helpers rather than hand-rolling: streaming responses are assembled via createStreamingExecution (@/providers/streaming-execution) and tool schemas via adaptOpenAIChatToolSchema / adaptAnthropicToolSchema (@/providers/tool-schema-adapter).

Thinking/reasoning models: streamed visibility + generated docs

If the entry has capabilities.thinking or capabilities.reasoningEffort, it appears in the autogenerated "Streamed thinking and tool calls" table on the Agent block docs page:

  • Anthropic-family (anthropic, azure-anthropic) thinking models MUST declare capabilities.thinking.streamed ('full' | 'summary' | 'none'). Verify against Anthropic's current thinking-display and streaming docs: visible thinking returned by the API is summarized, including when Sim opts models whose default display is omitted into display: 'summarized' on agent-events runs, so current Claude thinking models use 'summary'. Use 'full' only if future official API docs explicitly guarantee raw thinking deltas. bun run agent-stream-docs:check (CI) fails if the field is missing.
  • Other families usually omit the field and inherit the provider default in getThinkingStreamVisibility (Gemini/OpenAI → summaries; Bedrock/Meta → none; OpenAI-compatible vendors with documented reasoning fields → full deltas). Set it explicitly only when the model deviates from its family.
  • After inserting the entry, run bun run agent-stream-docs:generate and commit the regenerated apps/docs/content/docs/workflows/blocks/agent.mdx — CI diffs it.
  • Include the streamed value (with its source URL) in the verification report when set.
Wrong family entirely?
  • Embedding or rerank model → it does NOT go in the models[] array. Use EMBEDDING_MODEL_PRICING / RERANK_MODEL_PRICING in models.ts instead.
  • Brand-new provider (not just a new model under an existing one) → much larger surface: add the id to ProviderId in providers/types.ts, a registry entry in providers/registry.ts, a provider implementation under providers/<id>/ (assemble streaming responses with createStreamingExecution and wrap tool schemas with the @/providers/tool-schema-adapter helpers), an icon in components/icons.tsx, and the PROVIDER_DEFINITIONS block. That is beyond this skill — tell the user.

Step 5: Write, lint

bash
bun run lint
bun run agent-stream-docs:generate   # only when the entry has thinking/reasoningEffort

Lint must pass before you report done — fix the entry you wrote, never delete it to make lint pass.

Step 6: Verification report (mandatory format)

End with this exact structure:

markdown
### Verification — <model-id>

| Field | Value | Source URL | Status |
|---|---|---|---|
| `id` | `grok-4.3` | https://docs.x.ai/... | ✓ verified |
| `contextWindow` | 1,000,000 | https://docs.x.ai/... + https://openrouter.ai/... | ✓ verified (2 sources agree) |
| `input` | $1.25/M | https://docs.x.ai/... | ✓ verified |
| `cachedInput` | $0.20/M | https://cloudprice.net/... | ⚠️ single source |
| `output` | $2.50/M | https://docs.x.ai/... + https://openrouter.ai/... | ✓ verified |
| `capabilities.temperature` | `{ min: 0, max: 1 }` | matches sibling entries | — pattern-match only |
| `capabilities.reasoningEffort` | NOT SET | provider docs say API rejects it for this model | ✓ correctly omitted |
| `releaseDate` | 2026-04-30 | https://docs.x.ai/... announcement | ✓ verified |
| hosted/billing | hosted (`getHostedModels().includes(id)`) or BYOK-only | `providers/models.ts` | — confirmed intent |

**Disagreements**
- _none_ OR _OpenRouter says X, provider docs say Y — used Y per provider rule_

**Unverified fields**
- _none_ OR _<field>: could not find authoritative source — left as <X> based on sibling pattern; please confirm_

If any row is ⚠️ single-source or "unverified," state it plainly to the user and ask whether to proceed. Do not silently merge.

What to do if you cannot find a source

Omitting a field is not the same as verifying it. Any field you cannot confirm from a live fetch must be both omitted from the entry and listed as ❓ UNVERIFIED in the report's "Unverified fields" section, with the URLs you attempted. Then ask the user to confirm before merging.

  • Pricing missing → do NOT guess. Omit cachedInput. Mark ❓ UNVERIFIED. Ask the user for the price or the docs URL.
  • Context window missing → do NOT guess. Ask the user; mark ❓ UNVERIFIED.
  • Release date missing → omit the field; mark ❓ UNVERIFIED in the report.
  • Capability uncertain → omit the flag (safer than setting a dead/wrong one); mark ❓ UNVERIFIED so the user knows you didn't confirm it either way.

© simstudioai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .agents/skills/add-model of simstudioai/sim.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 546d4e7

Compare with similar skills

Add Model next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Add Model compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Add Model this skillsimstudioai/sim30k—~3.9kAutomated safety check: PassApache-2.0
Get API Docs with chubandrewyng/context-hub14k2 repos~775Automated safety check: PassMIT
Create SkillHyk260/PureChat5461 repos~823Automated safety check: PassMIT
Diataxis Docs Writercalf-ai/calfkit-sdk1491 repos~3kAutomated safety check: PassApache-2.0
Quota Provider Adapter Noteskunchenguid/quota-axi144—~4.2kAutomated safety check: PassMIT
Fact Checkerdaymade/claude-code-skills1.4k2 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Get API Docs with chub

    andrewyng/context-hub

    Fetches current documentation for third-party APIs and SDKs with the chub CLI before the agent writes code against them, instead of relying on remembered API shapes.

    14k GitHub starsUsed in 2 repos~775 tokens
    DevelopmentAuto-check passed
  • Create Skill

    Hyk260/PureChat

    Create a new skill in the current repository. An agent skill from Hyk260/PureChat.

    546 GitHub starsUsed in 1 repo~823 tokens
    DevelopmentAuto-check passed
  • Diataxis Docs Writer

    calf-ai/calfkit-sdk

    Write or improve software documentation using the Diátaxis framework — four documentation types (tutorials, how-to guides, reference, explanation), each serving a different user need.

    149 GitHub starsUsed in 1 repo~3k tokens
    DevelopmentAuto-check passed
  • Quota Provider Adapter Notes

    kunchenguid/quota-axi

    Reference of credential sources, quota windows, endpoint shapes, error recovery and quirks for each provider supported by the quota-axi tool.

    144 GitHub stars~4.2k tokensUpdated today
    DevelopmentAuto-check passed
  • Fact Checker

    daymade/claude-code-skills

    Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation.

    1.4k GitHub starsUsed in 2 repos~2.1k tokens
    DevelopmentAuto-check passed
  • Genie API Service Docs

    qualcomm/qai-appbuilder

    GenieAPIService technical documentation retrieval. An agent skill from qualcomm/qai-appbuilder.

    246 GitHub stars~840 tokensUpdated today
    DevelopmentAuto-check passed

More from simstudioai/sim

All 40 skills in this repo
  • Sim Helm

    simstudioai/sim

    Install, upgrade, and operate the Sim Helm chart on Kubernetes.

    30k GitHub stars~2.2k tokensUpdated today
    Auto-check passed
  • Add Column Type

    simstudioai/sim

    Add a new table column type to Sim — registry entry, icon, storage shape, coercion, and the behavioral hooks the grid and API read.

    30k GitHub stars~2.9k tokensUpdated today
    Auto-check passed
  • Add Enrichment

    simstudioai/sim

    Add a code-defined table enrichment (registry entry) under apps/sim/enrichments/ backed by an ordered provider cascade, ensuring every provider tool it calls has hosted-key support.

    30k GitHub stars~2.2k tokensUpdated today
    Auto-check passed
  • Add Hosted Key

    simstudioai/sim

    Add hosted API key support to a tool so Sim provides the key (metered and billed to the workspace) when a user has not brought their own.

    30k GitHub stars~3.4k tokensUpdated today
    Auto-check passed
  • Add Managed CLI

    simstudioai/sim

    Add or upgrade a curated, immutable managed CLI for Sim Function sandboxes, including client-safe catalog metadata, a pinned server-only installation recipe, checksum and executable verification…

    30k GitHub stars~2.4k tokensUpdated today
    Auto-check passed
  • Add Selector

    simstudioai/sim

    Add or update a Sim dynamic selector using the shared manifest, server attachment, and selectors.execute path.

    30k GitHub stars~1.7k tokensUpdated today
    Auto-check passed

Works with

Categories

Questions about Add Model

What does Add Model do?

Add a new LLM model to apps/sim/providers/models.ts with specs verified against the provider's live API docs (no hallucination). Add Model is an agent skill from simstudioai/sim.

When should I use Add Model?

Add Model fits situations like: tasks that involve Technical documentation.

How do I install Add Model in Claude Code?

Run `npx skills add simstudioai/sim --skill add-model -a claude-code`. Or copy the skill folder (.agents/skills/add-model in simstudioai/sim) into .claude/skills/add-model in your project. Claude Code loads it when a task matches its description.

How do I install Add Model in Codex?

Run `npx skills add simstudioai/sim --skill add-model -a codex`. Or copy the skill folder (.agents/skills/add-model in simstudioai/sim) into .agents/skills/add-model in your project. Codex loads it when a task matches its description.

Can I use Add Model in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add simstudioai/sim --skill add-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-model, .gemini/skills/add-model, .github/skills/add-model and .opencode/skills/add-model in your project.

What does Add Model need to run?

Going by SKILL.md and its folder, Add Model needs the command-line tools its instructions call (bun and rg).

Does Add Model access the network?

SKILL.md names 3 domains. In commands or code: docs.x.ai, openrouter.ai and cloudprice.net; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Add Model safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Add Model use?

Add Model is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Add Model use?

About 3.9k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Add Model?

Skills that share tags, products or a category with Add Model: Get API Docs with chub (andrewyng/context-hub, 14k stars), Create Skill (Hyk260/PureChat, 546 stars), Diataxis Docs Writer (calf-ai/calfkit-sdk, 149 stars) and Quota Provider Adapter Notes (kunchenguid/quota-axi, 144 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Add Model?

simstudioai (a GitHub organization) maintains it in simstudioai/sim, which has 29,792 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 8, 2026.

Source: simstudioai/sim on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.