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.
git clone --depth 1 https://github.com/Dkm0315/frappe-agentWrote 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/commands/dkm0315/frappe-agent/frappe-hrms)<a href="https://agentmods.dev/commands/dkm0315/frappe-agent/frappe-hrms"><img src="https://agentmods.dev/badge/commands/dkm0315/frappe-agent/frappe-hrms/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/commands/dkm0315/frappe-agent/frappe-hrms"><img src="https://agentmods.dev/badge/commands/dkm0315/frappe-agent/frappe-hrms.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.00062 |
| Opus 5 | $0.00000 | $0.00031 |
| Sonnet 5 | $0.00000 | $0.00012 |
| Haiku 4.5 | $0.00000 | $0.00006 |
Grade A, and why
frappe-hrms 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 10d 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.
What it actually says
Frappe HRMS
Treat the task as Frappe HRMS work.
- Identify attendance, leave, payroll, shifts, claims, recruitment, onboarding, appraisals, and HR reports.
- Protect salary, personal, attendance, and performance data.
- Call out jurisdiction-specific payroll assumptions.
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.
- 10d ago First seen · 8 lines · 0 tokens per session scan A 784421e3be9e
frappe-hrms is a command published in the GitHub repository Dkm0315/frappe-agent (24 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 62 tokens. 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.
Other commands, from other repositories
setup
Interactive auth setup wizard. Choose provider, configure OAuth, email, generate schema, create UI components — all in one command.
api-runtime-verify
Verify an implemented backend HTTP surface at runtime: per route, record the request actually made, the HTTP status, the response content-type, and the observed body shape, assert each response against the slice's acceptance behavior, classify the findings, and decide a PASS/FAIL/BLOCKED runtime gate. The probe's real…
api-contract-review
Review an API contract (endpoints, request/response shapes, error codes, auth model) BEFORE implementation for naming consistency, versioning, pagination, idempotency, and alignment with existing endpoints. Distinct from review-hard (post-implementation risk) and repo-consistency-sweep (pattern matching on written…
backend-system-design
Produce a staff-grade backend system-design RFC for the active task: a 12-section design document (problem, requirements, architecture, data model and storage, API contract, caching, scaling and bottlenecks, reliability and SLOs, security, observability, rollout and migration, trade-offs) for a new service, endpoint…
graphql-contract-review
Review a GraphQL schema and a Backend-for-Frontend (BFF) contract BEFORE implementation, against a GraphQL-specific checklist: schema shape and nullability (null-bubbling), errors-as-data unions, N+1 and DataLoader, query cost and depth limits, cursor-connection pagination, federation entity ownership, breaking-change…
doctor
Health check for existing auth setups. Diagnoses missing env vars, broken routes, dangerous code patterns, middleware issues, OAuth misconfig, and database connectivity.