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 tranhieutt/software_development_department --skill learnergit clone --depth 1 https://github.com/tranhieutt/software_development_departmentWrote 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/tranhieutt/software_development_department/learner)<a href="https://agentmods.dev/skills/tranhieutt/software_development_department/learner"><img src="https://agentmods.dev/badge/skills/tranhieutt/software_development_department/learner/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/tranhieutt/software_development_department/learner"><img src="https://agentmods.dev/badge/skills/tranhieutt/software_development_department/learner.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 | $0.00059 | $0.01203 |
| Opus 5 | $0.00030 | $0.00602 |
| Sonnet 5 | $0.00012 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
learner 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 8d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learner
Convert real SDD usage into durable operating knowledge.
Use this workflow to decide whether a lesson belongs in:
- an existing skill,
- a new skill,
.claude/memory/annotations.md,- another Tier 2 memory file,
- or no durable artifact.
Source Principles
This workflow adopts the Agent Skills guidance that durable skills come from real expertise, project artifacts, execution traces, and repeated refinement. Skills should capture team-specific process and failure modes, not generic best practices or deterministic glue better handled by scripts, hooks, or MCP.
Extraction Gate
Create or modify a skill only when at least one signal is present:
- Agent made a wrong choice despite a correct prompt.
- Existing skill fired but failed its mission.
- Needed skill did not fire because
descriptionwas weak or absent. - A teammate/user wrote the same long prompt, plan, or checklist a second time.
- Session repeated a costly investigation, setup, verification, or handoff loop.
- User corrected a project convention, team preference, or non-obvious edge case.
- Internal process, internal system, or proprietary data pattern must be reused.
Do not create a skill for:
- General advice the model already knows.
- One-off code snippets.
- Secrets, credentials, or environment-specific auth hacks.
- Simple deterministic checks better implemented as hooks, scripts, tests, or MCP.
- Large copied docs without a clear load condition.
Decision
Classify the lesson before editing:
| Lesson type | Target |
|---|---|
| Existing workflow missed a rule, edge case, or output shape | Update that skill body |
| Existing skill should have fired but did not | Tighten that skill description |
| Repeated team-specific process forms a coherent unit | Create or update a skill |
| Non-obvious caveat tied to a service/library/repo area | Use annotate memory |
| Broad preference or project operating rule | Update the right Tier 2 memory/doc |
| Deterministic repeated operation | Prefer tested script/hook/MCP; skill only orchestrates when needed |
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.
- 8d ago First seen · 146 lines · 59 tokens per session scan A a238d0de1242
learner is a skill published in the GitHub repository tranhieutt/software_development_department (72 stars, last pushed 4mo ago), licensed MIT. It adds 59 tokens to every session and 1,203 once invoked, about $0.0003 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 2026-09-03.
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