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 skills add Roshu18/bearstrike-ai --skill planninggit clone --depth 1 https://github.com/Roshu18/bearstrike-aiWrote 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/roshu18/bearstrike-ai/planning)<a href="https://agentmods.dev/skills/roshu18/bearstrike-ai/planning"><img src="https://agentmods.dev/badge/skills/roshu18/bearstrike-ai/planning/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/roshu18/bearstrike-ai/planning"><img src="https://agentmods.dev/badge/skills/roshu18/bearstrike-ai/planning.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 | $0.00016 | $0.00511 |
| Opus 5.5 | $0.00006 | $0.00204 |
| Sonnet 5.5 | $0.00003 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
planning 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 1mo 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
planning
Objective
Create a clear, low-noise attack plan before any active testing.
Mandatory pre-checks
- Read research-notes for current high-signal bug classes.
- Use traffic-proxy skill only after a concrete workflow hypothesis exists.
- Scope validation
- Confirm in-scope domains/IPs.
- Confirm out-of-scope exclusions.
- Risk tiering
- Public internet production targets: low-noise only first.
- Internal labs/CTF: broader active scans allowed.
- Initial target profile
- Domain, ASN, technology hints, auth surface, likely API presence.
Priority scoring model
Score each task by impact x confidence x feasibility (1-5 each).
- High score (60+): execute first.
- Medium (30-59): execute after first evidence.
- Low (<30): defer.
Output contract before scanning
Produce TODO list with:
- Phase: recon / enum / vuln / verify / report
- Tool: exact tool name
- Purpose: one sentence
- Success signal: what output means progress
- Stop condition: when to stop this task
Example TODO item
- Phase: recon
- Tool: subfinder
- Purpose: collect passive subdomains for attack surface
- Success signal: non-empty unique subdomain set
- Stop condition: duplicate-only output in 2 consecutive runs
Execution rule
Never run exploitation until at least one strong vulnerability signal is confirmed in recon/enum.
2024-2026 high-signal focus
Prioritize bug classes that repeatedly show high bounty impact:
- Broken access control (IDOR/BOLA/role boundary failures)
- Authentication/session logic flaws
- API data exposure and object-level authorization issues
- Misconfiguration and sensitive endpoint exposure
Endpoint-first planning
Before heavy scans, build a shortlist of high-value endpoint clusters:
- Account and profile endpoints
- Payment and transaction workflows
- Admin and internal API routes
- File upload and export/import endpoints
For each cluster, define:
- Expected actor (anonymous/user/admin/service)
- Expected object boundary (self-only/team/global)
- One negative test case (forbidden access)
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.
- 1mo ago First seen · 82 lines · 16 tokens per session scan A 84f14cdda158
planning is a skill published in the GitHub repository Roshu18/bearstrike-ai (8 stars, last pushed 6mo ago), licensed MIT. It adds 16 tokens to every session and 511 once invoked, about $0.0001 per session on Opus 5.5. 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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