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 skills/viknesh20-20/claude-code-tool-kit/estimatenpx skills add viknesh20-20/claude-code-tool-kit --skill estimategit clone --depth 1 https://github.com/viknesh20-20/claude-code-tool-kitWrote 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/viknesh20-20/claude-code-tool-kit/estimate)<a href="https://agentmods.dev/skills/viknesh20-20/claude-code-tool-kit/estimate"><img src="https://agentmods.dev/badge/skills/viknesh20-20/claude-code-tool-kit/estimate.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 | $0.00040 | $0.00600 |
| Opus 5 | $0.00020 | $0.00300 |
| Sonnet 5 | $0.00008 | $0.00120 |
| Haiku 4.5 | $0.00004 | $0.00060 |
Grade A, and why
estimate 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 4d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Effort Estimation
Context
!gh issue view $1 2>/dev/null || echo "Provide a task description or issue number"
Estimation Process
Step 1: Scope Analysis
- Read the task/issue description carefully
- Search the codebase to understand current state
- Identify all files, modules, and systems that would be affected
- Check for existing implementations that can be reused
Step 2: Task Breakdown
Decompose the work into subtasks. For each subtask:
| Subtask | Files Affected | Size | Confidence |
|---|---|---|---|
| ... | ... | S/M/L/XL | High/Med/Low |
Size Guide:
- S (Small): < 2 hours — single file change, straightforward logic
- M (Medium): 2-6 hours — multiple files, some complexity, needs tests
- L (Large): 1-2 days — cross-module changes, new patterns, significant testing
- XL (Extra Large): 3-5 days — architectural changes, new infrastructure, coordination needed
Step 3: Risk Assessment
Identify risks that could expand the estimate:
| Risk | Probability | Impact | Mitigation |
|---|---|---|---|
| ... | High/Med/Low | +S/+M/+L | ... |
Common risks:
- Unclear requirements → ask clarifying questions first
- Legacy code with no tests → add time for writing tests
- External dependencies → add time for integration
- Database migrations → add time for rollback planning
- API changes → add time for consumer coordination
Step 4: Dependencies
List any blockers or prerequisites:
- Other issues that must be completed first
- External services or APIs that must be available
- Team members who need to be consulted
- Infrastructure or access requirements
Step 5: Total Estimate
| Scenario | Estimate | Assumption |
|---|---|---|
| Best case | ... | Everything goes smoothly, no surprises |
| Likely case | ... | Normal amount of debugging and iteration |
| Worst case | ... | Major risks materialize |
Rules
- Be honest — over-optimistic estimates hurt more than conservative ones
- Include testing and review time in estimates
- Flag any assumptions you're making
- If the task is too vague to estimate, say so and list the questions that need answers
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.
- 4d ago First seen · 72 lines · 40 tokens per session scan A af8725b68581
estimate is a skill published in the GitHub repository viknesh20-20/claude-code-tool-kit (7 stars, last pushed 4mo ago), licensed MIT. It adds 40 tokens to every session and 600 once invoked, about $0.0002 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 skills, from other repositories
gh-file-issue
Use when filing a new Codewhale GitHub issue: turn a bug or idea into a well-formed, actionable issue with repro, acceptance criteria, labels, and milestone.
gh-treasure-hunt
Hunt the issue/PR queue for highest value-over-risk wins: clean focused community PRs, already-implemented issues to close, safe quick-fixes.
gh-assign-issues
Use to assign GitHub issues to a milestone and/or owners in bulk, verifying each.
triage
Triage open herdr GitHub issues into a concise decision-first Markdown table. Use when the user says "triage", asks to triage open issues, asks which issues need attention, or wants issue priority/recommendation lights for herdr.
sprint-planning
Plan implementation sprints with story selection, goal definition, and execution ordering.
kanban-management
Initialize and manage Kanban board state for feature workflow tracking.