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.
npx agentmods add skills/fullstack-phoenix/saas_kit/freeform-datanpx skills add fullstack-phoenix/saas_kit --skill freeform-datagit clone --depth 1 https://github.com/fullstack-phoenix/saas_kitWhat 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 | $0.00034 | $0.02074 |
| Opus 5 | $0.00017 | $0.01037 |
| Sonnet 5 | $0.00007 | $0.00415 |
| Haiku 4.5 | $0.00003 | $0.00207 |
Grade A, and why
freeform-data 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 yesterday.
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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Freeform Data
Use this skill when an AI feature should return text, code, markdown, or loose JSON instead of a validated schema.
Goal
- Reuse the shared
MyApp.Agentsconfiguration. - Keep a low-level
MyApp.Agents.LLMmodule for provider-specific requests. - Let task-specific modules build on top of that helper.
- Keep tests isolated with Mimic.
Root Agents Module
Use one shared root module for API keys and model names:
defmodule MyApp.Agents do
@moduledoc """
Central configuration for AI agents.
"""
def anthropic_key, do: Application.get_env(:my_app, :anthropic)[:api_key]
def openai_key, do: Application.get_env(:my_app, :openai)[:api_key]
def model(:haiku), do: "claude-haiku-4-5"
def model(:sonnet), do: "claude-sonnet-4-5"
def model(:gpt_5_mini), do: "gpt-5-mini"
def model(:gpt_5), do: "gpt-5.2"
def model(:gpt_4_1_mini), do: "gpt-4.1-mini"
end
Credential Placement
Do not put provider credentials in shared config/config.exs.
Keep local credentials in config/dev.exs:
config :my_app, :anthropic, api_key: System.get_env("ANTHROPIC_API_KEY")
config :my_app, :openai, api_key: System.get_env("OPENAI_API_KEY")
Low-level LLM Module
Keep one shared helper module for raw LLM calls:
defmodule MyApp.Agents.LLM do
import MyApp.Agents
@claude_url "https://api.anthropic.com/v1/messages"
@openai_url "https://api.openai.com/v1/chat/completions"
def claude(content, opts \\ [])
def claude("" <> content, opts) do
[%{role: "user", content: content}]
|> claude(opts)
end
def claude(messages, opts) when is_list(messages) do
model_name = Keyword.get(opts, :model, model(:haiku))
max_tokens = Keyword.get(opts, :max_tokens, 4_096)
extract_code = Keyword.get(opts, :extract_code, false)
extract_json = Keyword.get(opts, :extract_json, false)
Req.post(@claude_url,
headers: [
{"Content-Type", "application/json"},
{"x-api-key", anthropic_key()},
{"anthropic-version", "2023-06-01"}
],
receive_timeout: 90_000,
json: %{
max_tokens: max_tokens,
model: model_name,
messages: messages
}
)
|> parse()
|> maybe_extract_code(extract_code)
|> maybe_extract_json(extract_json)
end
def openai(content, opts \\ [])
def openai("" <> content, opts) do
[%{role: "user", content: content}]
|> openai(opts)
end
def openai(messages, opts) when is_list(messages) do
model_name = Keyword.get(opts, :model, model(:gpt_5_mini))
reasoning_effort = Keyword.get(opts, :reasoning_effort, "medium")
max_tokens = Keyword.get(opts, :max_tokens, 4_096)
extract_code = Keyword.get(opts, :extract_code, false)
extract_json = Keyword.get(opts, :extract_json, false)
prediction = Keyword.get(opts, :prediction)
Req.post(@openai_url,
headers: [
{"Content-Type", "application/json"},
{"Authorization", "Bearer #{openai_key()}"}
],
receive_timeout: 90_000,
json:
%{
model: model_name,
max_completion_tokens: max_tokens,
messages: messages
}
|> maybe_add_reasoning_effort(reasoning_effort, model_name)
|> maybe_add_prediction(prediction)
)
|> parse()
|> maybe_extract_code(extract_code)
|> maybe_extract_json(extract_json)
end
defp maybe_add_prediction(json, "" <> content) do
json
|> Map.delete(:max_completion_tokens)
|> Map.put(:prediction, %{content: content, type: "content"})
|> Map.put(:model, model(:gpt_4_1_mini))
end
defp maybe_add_prediction(json, _), do: json
defp maybe_add_reasoning_effort(json, "" <> reasoning_effort, model_name)
when model_name in [model(:gpt_5), "o4-mini", "o3", "o3-mini"] do
Map.put(json, :reasoning_effort, reasoning_effort)
end
defp maybe_add_reasoning_effort(json, _, _), do: json
defp parse({:ok, %{body: %{"content" => [content | _]}}}) do
case content do
%{"text" => text, "type" => type} -> {:ok, %{content: text, type: type}}
_ -> {:error, %{content: "No result"}}
end
end
defp parse({:ok, %{body: %{"choices" => [choice | _]}}}) do
case choice do
%{"message" => %{"content" => content}} -> {:ok, %{content: content}}
_ -> {:error, %{content: "No result"}}
end
end
defp parse(_), do: {:error, %{content: "No result"}}
defp maybe_extract_code({:ok, %{content: content}}, true) do
{:ok, %{content: extract_code(content)}}
end
defp maybe_extract_code(result, _), do: result
defp maybe_extract_json({:ok, %{content: content}}, true) do
{:ok, %{content: extract_json(content)}}
end
defp maybe_extract_json(result, _), do: result
defp extract_code(content) do
content
|> String.replace("```elixir", "```")
|> String.replace("```javascript", "```")
|> String.replace("```json", "```")
|> String.trim()
|> String.split("```")
|> case do
[_, code | _] -> code
[text] -> text
end
end
def extract_json(text_or_json) do
text_or_json
|> String.replace("```json", "```")
|> String.trim()
|> String.split("```")
|> case do
[_, json | _] -> json
[json] -> json
end
|> Jason.decode!()
rescue
_ -> %{}
end
end
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.
- yesterday First seen · 263 lines · 34 tokens per session scan A c4317aab2dfd
freeform-data is a skill published in the GitHub repository fullstack-phoenix/saas_kit (2 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 2,074 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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