Borrowing it
Nothing to install: this file belongs to Shashank2577/hesoyam-for-claude-code. 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/Shashank2577/hesoyam-for-claude-code/main/.claude/skills/research-sprint/SKILL.mdgit clone --depth 1 https://github.com/Shashank2577/hesoyam-for-claude-codeWrote 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/shashank2577/hesoyam-for-claude-code/research-sprint)<a href="https://agentmods.dev/skills/shashank2577/hesoyam-for-claude-code/research-sprint"><img src="https://agentmods.dev/badge/skills/shashank2577/hesoyam-for-claude-code/research-sprint/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/shashank2577/hesoyam-for-claude-code/research-sprint"><img src="https://agentmods.dev/badge/skills/shashank2577/hesoyam-for-claude-code/research-sprint.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 | $0.00013 | $0.00509 |
| Opus 5 | $0.00006 | $0.00254 |
| Sonnet 5 | $0.00003 | $0.00102 |
| Haiku 4.5 | $0.00001 | $0.00051 |
Grade A, and why
research-sprint 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 12d 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
$VAULT_PATH defaults to ~/Documents/obsidian-vault. Override by setting VAULT_PATH in your environment or passing --vault-path during install.
You are conducting a timeboxed research sprint. Follow this process exactly.
Step 1: Define the question. Ask the user:
- What specifically do you need to decide?
- What are the constraints (budget, timeline, team skills, infrastructure)?
- What output format do you need? (ADR, comparison matrix, team briefing, all of the above?)
Step 2: Research. Search across multiple dimensions:
- Current industry best practices for this problem
- Top 3 approaches with their tradeoffs
- How each approach integrates with the user's existing stack
- Real-world production experience (blog posts, conference talks, post-mortems)
- Failure modes and risks for each approach
Save findings as structured markdown files in research/[topic]/ under the current project root:
findings.md— Raw research notes organized by dimensioncomparison-matrix.md— Side-by-side comparison tablerecommendation.md— Your recommended approach with rationale
Step 3: Synthesize. Create a final deliverable based on the requested output format:
- ADR: Use the standard ADR format (Context, Options Considered, Decision, Rationale, Consequences). Save to the vault if Obsidian is configured.
- Comparison matrix: Weighted scoring table with clear winner highlighted.
- Team briefing: Executive summary (5 bullet points max) + detailed appendix.
Step 4: Capture.
- Save the research to Obsidian vault if configured (
$VAULT_PATH/03_Resources/research/[topic]/) - Add frontmatter with type: research, topic, date, status, decision
- Create claude-mem observation summarizing the decision (skip if claude-mem is not installed)
Rules:
- Cite sources for every claim. "I think" is not a source.
- Present tradeoffs honestly. Every option has downsides — state them clearly.
- Make a clear recommendation. Don't leave the user with "it depends" unless it truly does, and then specify what it depends on.
- Stay within the user's constraints. Don't recommend a $50K/year solution to a solo developer.
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.
- 12d ago First seen · 46 lines · 13 tokens per session scan A 908401b29a53
research-sprint is a skill published in the GitHub repository Shashank2577/hesoyam-for-claude-code (11 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 509 once invoked, about $0.0001 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.
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