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/wardawgmalvicious/agent-config/pbir-clinpx skills add wardawgmalvicious/agent-config --skill pbir-cligit clone --depth 1 https://github.com/wardawgmalvicious/agent-configWrote 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/wardawgmalvicious/agent-config/pbir-cli)<a href="https://agentmods.dev/skills/wardawgmalvicious/agent-config/pbir-cli"><img src="https://agentmods.dev/badge/skills/wardawgmalvicious/agent-config/pbir-cli.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 | $0.00187 | $0.01614 |
| Opus 5 | $0.00093 | $0.00807 |
| Sonnet 5 | $0.00037 | $0.00323 |
| Haiku 4.5 | $0.00019 | $0.00161 |
Grade A, and why
pbir-cli 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pbir CLI — Verb Index
Agent-first CLI for manipulating local Power BI reports in PBIR format. Install separately: uv tool install pbir-cli. Verify with pbir --version.
Run discovery before every mutation. pbir schema describe <type>.<container> is the canonical way to confirm a property exists before pbir set. Run pbir validate after every mutation.
Path Syntax
Report.Report/Page.Page/Visual.Visual
- Type suffixes (
.Report,.Page,.Visual) are REQUIRED - Glob patterns:
**/*.Visual,**/card*.Visual - Property dot-notation after path:
Visual.Visual.title.fontSize - Reports must be local PBIR — use
pbir downloadto fetch from Fabric first
Global Flags
| Flag | Purpose |
|---|---|
--quiet / -q |
Suppress animations, tips, spinners (prefer for scripts) |
--debug |
Tracebacks, timing, path resolution to stderr |
--version / -V |
Show version |
--show-legacy |
Include legacy non-PBIR reports in listings |
Verb–Noun Groups
| Group | Entry commands | Detail |
|---|---|---|
| Discovery | pbir ls, pbir tree, pbir find, pbir cat, pbir get |
references/REFERENCE.md § Discovery |
| Schema | pbir schema types, pbir schema containers, pbir schema describe, pbir schema check, pbir schema upgrade |
references/REFERENCE.md § Schema |
| Property get/set | pbir set, pbir get, pbir visuals properties, pbir visuals format |
references/REFERENCE.md § Property |
| Report | pbir new report, pbir report rebind, pbir report convert, pbir report merge, pbir validate, pbir backup, pbir restore |
references/REFERENCE.md § Report |
| Pages | pbir pages …, pbir add page |
references/REFERENCE.md § Pages |
| Visuals | pbir add visual, pbir visuals … |
references/REFERENCE.md § Visuals |
| Conditional formatting | pbir visuals cf …, pbir visuals format-field, pbir visuals format-state |
references/REFERENCE.md § CF |
| Filters | pbir filters …, pbir add filter |
references/REFERENCE.md § Filters |
| Fields | pbir fields … |
references/REFERENCE.md § Fields |
| Theme | pbir theme … |
references/REFERENCE.md § Theme |
| DAX | pbir dax measures …, pbir dax viscalcs … |
references/REFERENCE.md § DAX |
| Bookmarks & annotations | pbir bookmarks …, pbir annotations …, pbir add annotation |
references/REFERENCE.md § Bookmarks |
| Connection / publish | pbir connect, pbir profile, pbir download, pbir publish, pbir open |
references/REFERENCE.md § Connection |
| Model inspection | pbir model … |
references/REFERENCE.md § Model |
| Removal | pbir rm |
references/REFERENCE.md § Removal |
| Batch | pbir batch run, pbir validate |
references/REFERENCE.md § Batch |
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.
- yesterday Changed · +3 lines cac00d29a05f
- 5d ago First seen · 96 lines · 187 tokens per session scan A c713dcec5bb5
pbir-cli is a skill published in the GitHub repository wardawgmalvicious/agent-config (1 stars, last pushed yesterday), licensed MIT. It adds 187 tokens to every session and 1,614 once invoked, about $0.0009 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
email-sequence
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle…
llm-app-patterns
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
qa-test-planner
Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.
guidance
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework.
gemini-api-agent-platform
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK for enterprise AI applications. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
skypilot-multi-cloud-orchestration
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.