Borrowing it
Nothing to install: this file belongs to r5rana/agentware. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/r5rana/agentware/main/.claude/skills/self-improvement/SKILL.mdgit clone --depth 1 https://github.com/r5rana/agentwareWrote 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/r5rana/agentware/self-improvement)<a href="https://agentmods.dev/skills/r5rana/agentware/self-improvement"><img src="https://agentmods.dev/badge/skills/r5rana/agentware/self-improvement.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 | $0.00000 | $0.03097 |
| Opus 5 | $0.00000 | $0.01548 |
| Sonnet 5 | $0.00000 | $0.00619 |
| Haiku 4.5 | $0.00000 | $0.00310 |
Grade B, and why
self-improvement scanned grade B with 1 finding 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 7d 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.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
--category skills` (the user's external skills) and `ls .claude/skills/` (the How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Improvement Skill — How agentware Grows Its Own Skills
When to invoke: at the end of any task or iteration, when you notice you just did something you'll likely do again — or when the post-phase assessment (run by the execution agent) extracts knowledge from a worklog. agentware treats incidental learnings as cheap (just write them) and skill promotion as a small, auditable negotiation with the user.
Why this skill exists
Without an explicit promotion procedure, knowledge dies in three places:
- In conversation, when the agent says "ah, I figured out X" but never writes it down.
- In
assessment.md, when the post-phase assessment extracts a learning and nothing moves it into the live knowledge base. - In
worklog.md, where worklogs grow long and the reusable bits get buried.
This skill closes the loop: every learning lands somewhere the next agent can find it, with the right level of authority. Learnings auto-promote, skills ask once, steering always asks.
The decision tree
After completing a task (or reviewing a worklog), classify any new knowledge:
Did I learn something?
├── No → continue to next task
└── Yes → Is it project-specific?
├── Yes → write learning to the EXTERNAL dir (auto, no permission)
└── No → Is it a reusable procedure (≥2 steps, applies to many tasks)?
├── Yes → write skill to the EXTERNAL dir (auto, just inform the user)
└── No → Is it an always-true rule for the PACKAGE itself?
├── Yes → package/steering change → EXPLICIT request + !! WARNING !!
└── No → write learning to the EXTERNAL dir (auto)
Writing to the user's external dir is always safe and needs no permission — it's
their own space and never touches the orchestrator. Only changing the PACKAGE
(steering/skills/loop) requires an explicit request and the !! WARNING !!.
Examples
| Discovery | Type | Where it goes | Permission |
|---|---|---|---|
| "This app's dev server runs on port 4173" | Project-specific fact | learnings/<project>-setup.md |
None (auto) |
| "To debug a hydration mismatch in Next.js: do these 5 steps" | Reusable procedure | <knowledge-dir>/skills/debug-hydration/SKILL.md (external) |
Ask user once |
"Always run npm ci rather than npm install on CI" |
Always-true rule | AGENTS.md (package — self-extension) |
Explicit + !! WARNING !! |
"Stuck Docker container? docker rm -f X then retry" |
One-off fix | learnings/docker-gotchas.md |
None (auto) |
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.
- 7d ago First seen · 232 lines · 0 tokens per session scan B 6b53a8b30e6c
self-improvement is a skill published in the GitHub repository r5rana/agentware (24 stars, last pushed 21d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,097 tokens. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.