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/tony/skills/case-study-internalnpx skills add tony/skills --skill case-study-internalgit clone --depth 1 https://github.com/tony/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/tony/skills/case-study-internal)<a href="https://agentmods.dev/skills/tony/skills/case-study-internal"><img src="https://agentmods.dev/badge/skills/tony/skills/case-study-internal.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 | $0.00033 | $0.00708 |
| Opus 5 | $0.00016 | $0.00354 |
| Sonnet 5 | $0.00007 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
case-study-internal 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.
This is a copy
86% identical to business-case-study-internal — 36 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Internal Case Study (tier 2)
Turn a run package into a narrative case study for internal circulation: what happened, what it measured, what other teams can take from it. Tier 2: internal team and repo names allowed; individuals anonymized to roles. Value is engineer-hours, cycle time, and capacity; never money.
Read ../../references/interim-format.md first — it
defines run location and the completeness gate. Defer these rendering
references until the gate passes; a refused render never loads them:
../../references/provenance.md— tag rendering, anti-inflation rules, the no-currency contract.../../references/audiences.md— the tier-2 contract.
User arguments: $ARGUMENTS
Context
Recent runs:
!sh -c 'ls -dt "$HOME"/Documents/*/business/ /mnt/c/Users/*/Documents/*/business/ 2>/dev/null' | head -5 | grep . || echo "(no runs found)"
Procedure
1. Locate the run
Use the $ARGUMENTS path if given, else the newest run per
interim-format.md. Confirm the choice with the user.
2. Completeness gate
Run the completeness gate from interim-format.md. Refuse to render
from an incomplete package; list what is missing and stop.
3. Render the case study
Read the deferred references above, then write
<run>/reports/case-study-internal.md as a narrative in this
fixed order:
- Situation — the team, the recurring task, why it cost enough to act on.
- What was built — the skill or workflow, its build time (tagged), and who maintains it.
- Measured outcomes — every figure tagged, denominator stated, window pinned. Include the costs: verification time, failed runs, maintenance.
- Lessons — what worked, what did not, what the team would do differently.
- How other teams can replicate — prerequisites, the expected ramp (and the excluded novelty window), and where results are likely to differ.
Anonymize individuals to roles. Team and repo names stay.
Output
Open with a one-line hero (✓ Case study: <one-line outcome with tag>, ✓ Evidence report: <supported claim, unknowns named>, or
⚠ Refused: <reason>), then exactly these sections:
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 · 81 lines · 33 tokens per session scan A 7f4da25f0b3c
case-study-internal is a skill published in the GitHub repository tony/skills (2 stars, last pushed 6d ago), licensed MIT. It adds 33 tokens to every session and 708 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to business-case-study-internal, differing in 36 lines, and is treated as a copy.
Other skills, from other repositories
postgres-database-migration
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. Trigger when user asks to: Test a schema migration before applying it to production Add, remove, or rename columns safely on a live table Change a column's data…
design-postgis-tables
Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications.
migrate-postgres-tables-to-hypertables
Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. Trigger when user asks to: Migrate or convert PostgreSQL tables to hypertables Execute hypertable migration with minimal downtime Plan blue-green migration for large tables Validate…
pgvector-semantic-search
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. Trigger when user asks to: Store or search vector embeddings in PostgreSQL Set up semantic search, similarity search, or nearest neighbor search Create HNSW or IVFFlat indexes for vectors…
setup-timescaledb-hypertables
Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. Trigger when user asks to: Create or design SQL schemas/tables AND…
postgres-hybrid-text-search
Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). Trigger when user asks to: Combine keyword and semantic search Implement hybrid search or multi-modal retrieval Use BM25/pgtextsearch with pgvector together Implement RRF (Reciprocal…