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 commands/ankushdixit/claude-plugins/learn-showgit clone --depth 1 https://github.com/ankushdixit/claude-pluginsWhat 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 | $0.00005 | $0.00360 |
| Opus 5 | $0.00003 | $0.00180 |
| Sonnet 5 | $0.00001 | $0.00072 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
learn-show 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 2d 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
Show Learnings
View captured learnings with optional filtering.
Usage
Parse $ARGUMENTS for filters and run the show-learnings command:
sk learn-show "$@"
Filter Options
-
--category <category>- Filter by category:architecture_patterns- Design decisions and patternsgotchas- Edge cases and pitfallsbest_practices- Effective approachestechnical_debt- Areas needing improvementperformance_insights- Optimization learningssecurity- Security-related discoveries
-
--tag <tag>- Filter by specific tag (e.g.,python,fastapi,cors) -
--session <number>- Show learnings from specific session number
Examples
Show all learnings:
sk learn-show
Show only gotchas:
sk learn-show --category gotchas
Show learnings tagged with "fastapi":
sk learn-show --tag fastapi
Show learnings from session 5:
sk learn-show --session 5
Combine filters (gotchas from session 5):
sk learn-show --category gotchas --session 5
Display Format
The command will display learnings in organized format showing:
- Category grouping
- Learning content
- Tags (if any)
- Session number where captured
- Timestamp
- Learning ID
Present the output to the user in a clear, readable format.
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.
- 2d ago First seen · 76 lines · 0 tokens per session scan A f16cd7904373
learn-show is a command published in the GitHub repository ankushdixit/claude-plugins (3 stars, last pushed 7mo ago), licensed MIT. It adds 5 tokens to every session and 360 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
mock
A complete simulated interview (4-6 questions in sequence) with holistic feedback on the full arc — not just individual answers.
review
View your learning progress — quiz scores, weak areas, and what to study next.
start-1-7
Start Lesson 1.7 - Project Memory.
edit-textbook-chapter
Edit a textbook-style chapter, following evidence-based writing instructions.
explain
Explain code, concepts, or system behavior with adjustable depth levels.
onboard
This command acts as an expert technical mentor to help you rapidly understand a new codebase, generating a comprehensive "Survival Guide" for the project.