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 lubusIN/frappe-skills --skill reportsgit clone --depth 1 https://github.com/lubusIN/frappe-skillsWrote 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/lubusin/frappe-skills/reports)<a href="https://agentmods.dev/skills/lubusin/frappe-skills/reports"><img src="https://agentmods.dev/badge/skills/lubusin/frappe-skills/reports/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/lubusin/frappe-skills/reports"><img src="https://agentmods.dev/badge/skills/lubusin/frappe-skills/reports.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 307 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.02195 |
| Opus 5 | $0.00019 | $0.01097 |
| Sonnet 5 | $0.00008 | $0.00439 |
| Haiku 4.5 | $0.00004 | $0.00219 |
Grade A, and why
reports 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 11d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Frappe Reports
Build reports using Report Builder, Query Reports (SQL), or Script Reports (Python + JS).
When to use
- Creating data analysis or summary reports
- Building SQL-based query reports
- Implementing complex reports with Python logic and JS UI
- Adding custom filters, formatters, and charts to reports
- Creating printable report formats
Inputs required
- Report purpose and data requirements
- Source DocType(s) for the report
- Filter requirements
- Column definitions (fields, types, formatting)
- Whether report is standard (app-bundled) or custom (site-specific)
Procedure
0) Choose report type
| Type | Complexity | Code Required | Best For |
|---|---|---|---|
| Report Builder | Low | None | Simple field selection, grouping, sorting |
| Query Report | Medium | SQL only | Direct SQL queries, joins, aggregations |
| Script Report | High | Python + JS | Complex logic, computed fields, dynamic filters |
1) Report Builder
Create via UI with no code:
- Navigate to the Report list → New Report
- Select Reference DocType
- Choose Report Type = "Report Builder"
- Add columns, filters, sorting, and grouping via the builder UI
2) Query Report
Reports using raw SQL queries:
- Create Report → Type = "Query Report"
- Set Reference DocType (controls permissions)
- Write SQL query
SELECT
`tabSales Order`.name AS "Sales Order:Link/Sales Order:200",
`tabSales Order`.customer AS "Customer:Link/Customer:200",
`tabSales Order`.transaction_date AS "Date:Date:120",
`tabSales Order`.grand_total AS "Grand Total:Currency:150",
`tabSales Order`.status AS "Status:Data:100"
FROM `tabSales Order`
WHERE `tabSales Order`.docstatus = 1
{% if filters.company %}
AND `tabSales Order`.company = %(company)s
{% endif %}
{% if filters.from_date %}
AND `tabSales Order`.transaction_date >= %(from_date)s
{% endif %}
ORDER BY `tabSales Order`.transaction_date DESC
Column format in SELECT: "Label:Fieldtype/Options:Width"
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.
- 11d ago First seen · 311 lines · 39 tokens per session scan A 6a5bc54df9be
reports is a skill published in the GitHub repository lubusIN/frappe-skills (58 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 2,195 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 2026-08-30.
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