Borrowing it
Nothing to install: this file belongs to aimasteracc/tree-sitter-analyzer. 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/aimasteracc/tree-sitter-analyzer/main/.claude/skills/tsa-landing/SKILL.mdgit clone --depth 1 https://github.com/aimasteracc/tree-sitter-analyzerWrote 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/aimasteracc/tree-sitter-analyzer/tsa-landing)<a href="https://agentmods.dev/skills/aimasteracc/tree-sitter-analyzer/tsa-landing"><img src="https://agentmods.dev/badge/skills/aimasteracc/tree-sitter-analyzer/tsa-landing.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00142 | $0.01422 |
| Opus 5 | $0.00071 | $0.00711 |
| Sonnet 5 | $0.00028 | $0.00284 |
| Haiku 4.5 | $0.00014 | $0.00142 |
Grade A, and why
tsa-landing 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tsa-landing — Land in any repo in <3s
First action on entering a new repo. Replaces 6 separate bootstrap calls (~15k tokens) with 3-4 parallel calls (~2k tokens). 92% token saved.
When to use
- You just entered an unfamiliar project (no Claude.md / no skim yet)
- You return after long gap and need "what's the state?"
- User asks any of: "what is this project / where do I start / what's the entry / recent changes / health"
Don't use when:
- You already have full context (just continue working)
- User wants to read source — use
structure action=readdirectly
Procedure
Step 1 — Verify tools available
uv run python -m tree_sitter_analyzer --check-tools --format json | head -5
If fd or rg missing, stop and tell user how to install.
Step 2 — Fan-out 4 MCP calls (in single message, parallel)
Call these 4 tools in ONE message (parallel tool use):
project action=overview(no args) — project_card + entry_pointshealth action=projectwithmax_files: 5— grade distribution + weakest dimensionedit action=impactwithmode: "branch"— recent_signals (last commit, ahead-of-main)project action=workflow(no args) — current_phase + recommended_commands
Step 3 — Fold and emit decision_surface
Combine into single Decision Surface:
{
"project_card": {
"name": <from project action=overview project_root basename>,
"primary_language": <key with the highest count in project action=overview summary.by_language — it is a {language: file_count} dict sorted descending, so the first key>,
"language_mix": <from project action=overview summary.by_language — first 3 keys of the {language: file_count} dict>,
"size": {
"files": <from project action=overview summary.total_files>,
"loc": <from project action=overview summary.total_lines>
}
},
"entry_points": <from project action=overview entry_points>,
"recent_signals": {
"last_commit": <git log -1 --oneline via Bash>,
"ahead_of_origin": <git rev-list --count via Bash>,
"uncommitted_files": <git status --short | wc -l via Bash>,
"branch": <git branch --show-current via Bash>
},
"health": {
"verdict": <from health action=project verdict>,
"risk": <from health action=project agent_summary.risk>,
"grade_distribution": <from health action=project grade_distribution>,
"weakest_dimension": <from health action=project weakest_dimension>
},
"top_files_to_know": [
"AGENTS.md",
"CLAUDE.md",
<from project action=overview entry_points>,
<top 3 from health action=project top_refactoring_targets>
],
"agent_next_step": {
"if_asked_what_is_this":
"Read AGENTS.md (canonical contracts) + docs/CODEMAPS/architecture.md (topology). Stop after 2k tokens.",
"if_asked_to_add_feature":
"Call project action=workflow → follow phase_order. Use TDD (write test first).",
"if_asked_to_fix_bug":
"Call health action=patterns file_path=<file> → edit action=refactor file_path=<file>. Cross-ref nav action=lineage if symbol-level.",
"if_asked_about_test_status":
"Run: uv run pytest -q (5-min cap). Project enforces xdist parallel, ~5min for 15k tests."
},
"summary_line": "<project> files=<N> py=<X%> grade=<G> recent=<commit_subj>",
"verdict": "INFO"
}
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 · 138 lines · 142 tokens per session scan A ded7e072cd7e
tsa-landing is a skill published in the GitHub repository aimasteracc/tree-sitter-analyzer (49 stars, last pushed today), licensed MIT. It adds 142 tokens to every session and 1,422 once invoked, about $0.0007 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 2026-08-30.
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