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 skills add OutlitAI/outlit-sdk --skill outlitgit clone --depth 1 https://github.com/OutlitAI/outlit-sdkWrote 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/outlitai/outlit-sdk/outlit)<a href="https://agentmods.dev/skills/outlitai/outlit-sdk/outlit"><img src="https://agentmods.dev/badge/skills/outlitai/outlit-sdk/outlit.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00039 | $0.01217 |
| Opus 5 | $0.00019 | $0.00609 |
| Sonnet 5 | $0.00008 | $0.00243 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
outlit 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 4d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outlit
Use Outlit tools to ground customer intelligence work in customer data. Outlit joins product activity, conversations, billing, and web signals into a unified customer context graph and timeline for agents.
Use the registered outlit_* tools as the interface. Do not tell the user to install the Outlit CLI or configure MCP from inside Pi unless they explicitly ask about a different agent environment.
Do not invent customer state when Outlit can answer it. Call out sparse or messy data instead of overstating confidence.
Tool Choice
- Use
outlit_list_customersto discover customers for portfolio, segment, risk, revenue, trial, or account-health questions. - Use
outlit_list_usersfor user-level questions or when a customer answer depends on individual users. - Use
outlit_get_customerbefore deep analysis of a named customer or account. - Use
outlit_get_timelinewhen order, recency, activity sequence, meetings, messages, product usage, support, or billing chronology matters. - Use
outlit_list_factsto browse structured account facts, known signals, open issues, health indicators, relationship notes, activation, billing, or renewal context. Narrow withstatus,sourceTypes, andfactTypeswhen you know what evidence class you need. - Use
outlit_get_factwhen you already have a fact id and need the canonical fact payload. - Use
outlit_search_customer_contextfor fuzzy or thematic questions such as pricing concern, blocked integration, not using, renewal, champion left, negative sentiment, expansion, implementation, or support escalation. - Use
outlit_list_sourcesto discover the source artifacts available for a customer before retrieving one in full. - Use
outlit_get_sourcewhen a fact or search result needs stronger evidence from the underlying source artifact. - Use
outlit_get_customer_featuresfor exact, customer-level Feature observations. Treat unavailable coverage as unknown, not zero usage. - Use
outlit_list_featuresto inspect the confirmed workspace taxonomy, historical evidence, eligible sources, and event candidates. - Use
outlit_create_featureonly when the user explicitly asks to configure one confirmed product capability from one exact event rule. Outlit creates the supporting usage metrics internally. - Use
outlit_archive_featureonly when the user explicitly asks to archive a feature and supplies the current opaque id and revision. The MVP has no restore operation and rejects archiving the final active feature.
What ships with it
1 file 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.
- 4d ago Changed cdcf3de1c041
- 8d ago First seen · 85 lines · 39 tokens per session scan A a5b4250bd24a
outlit is a skill published in the GitHub repository OutlitAI/outlit-sdk (6 stars, last pushed 2d ago), licensed Apache-2.0. It adds 39 tokens to every session and 1,217 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.
Other skills, from other repositories
opik-diagnose
Surface the Opik traces worth a developer's attention, ranked by signal — errors, failed tool calls, latency, regressions, and low online-eval scores — plus Diagnostics issues. Reads live/production traces via the SDK (searchtraces and agentinsights) and works with no MCP; uses the MCP issue entity when connected.…
client-scripts
Write ServiceNow client scripts (onLoad/onChange/onSubmit/onCellEdit) using gform, guser, GlideAjax, field visibility/mandatory toggles, and validation with debounced server calls.
agoragentic-transaction-assurance
Prepare, evaluate, and reconcile autonomous agent transactions without self-granting payment or owner authority. Use when an agent must bind principal authority, seller terms, payment evidence, execution, delivered outcome, and reconciliation; handle paid retries safely; or prepare an authority request for owner…
agreement-setup
Set up a bKash tokenized agreement for repeat charges and check its status.
planfix-api
A Planfix CRM integration for managing tasks and contacts. A CRM is a system for organizing customer and business relationships.
maya-shot-export
Pipeline stage — shot-level export: frame ranges, cameras, FBX / Alembic packaging for editorial. Use when packaging shot data for downstream departments. Not for full pipeline publish (maya-pipeline) or scene assembly (maya-scene-assembly).