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/rajitsaha/100xprism/issuenpx skills add rajitsaha/100xprism --skill issuegit clone --depth 1 https://github.com/rajitsaha/100xprismWrote 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/rajitsaha/100xprism/issue)<a href="https://agentmods.dev/skills/rajitsaha/100xprism/issue"><img src="https://agentmods.dev/badge/skills/rajitsaha/100xprism/issue.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 5.1 | $0.00046 | $0.02494 |
| Opus 5 | $0.00023 | $0.01247 |
| Sonnet 5 | $0.00009 | $0.00499 |
| Haiku 4.5 | $0.00005 | $0.00249 |
Grade A, and why
issue scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue — Investigate & Create Detailed GitHub Issue
Given an observation, bug, or gap: investigate multi-dimensionally, find the root cause, plan the resolution, and create a detailed actionable GitHub issue.
Do NOT ask for permission — investigate thoroughly, then create the issue.
Phase 1 — Codebase Investigation
Understand the problem in full context before forming any opinion.
PROJECT_ROOT=$(git rev-parse --show-toplevel); cd "$PROJECT_ROOT"
git log --oneline -20
git status
# Detect the stack so later steps don't assume GCP/npm (canonical block — source: _lib/reference.md)
INSTRUCTION_FILE=$(for f in CLAUDE.md AGENTS.md .cursorrules; do [ -f "$PROJECT_ROOT/$f" ] && echo "$PROJECT_ROOT/$f" && break; done)
CLOUD=""
if command -v gcloud >/dev/null 2>&1 && gcloud config get-value project >/dev/null 2>&1; then CLOUD=gcp; fi
[ -z "$CLOUD" ] && grep -rqiE "aws_|amazonaws|::aws" "$PROJECT_ROOT"/terraform "$PROJECT_ROOT"/infra "$PROJECT_ROOT"/cdk.json 2>/dev/null && CLOUD=aws
[ -z "$CLOUD" ] && [ -n "$INSTRUCTION_FILE" ] && grep -qiE "gcloud|Cloud Run|Firebase" "$INSTRUCTION_FILE" && CLOUD=gcp
CI_SYSTEM=""; ls "$PROJECT_ROOT"/.github/workflows/*.y*ml >/dev/null 2>&1 && CI_SYSTEM=github-actions
echo "stack: cloud=${CLOUD:-none} ci=${CI_SYSTEM:-none}"
- Search for all code relevant to the observation (routes, components, services, DB queries, migrations, tests)
- Read the relevant source files — never guess at behavior
- Check recent commits in the affected area:
git log --oneline --since="60 days ago" -- <relevant-paths> - Check for existing related issues (only if
ghis available). Pull titles and bodies, then match on meaning, not just a keyword grep — a dupe often uses different words for the same root cause:
If an existing issue describes the same underlying problem, reference or update it instead of filing a duplicate.command -v gh >/dev/null 2>&1 && gh issue list --state all --limit 100 \ --json number,title,body -q '.[] | "#\(.number) \(.title)\n\(.body)\n---"' 2>/dev/null - Check current test coverage for the affected code paths
- If a production issue and
CLOUD=gcp, check Cloud Run logs (resolve the project from gcloud config — never pass a literal placeholder):
For other providers, read logs the platform-appropriate way (AWS:if [ "$CLOUD" = gcp ]; then PROJECT=$(gcloud config get-value project 2>/dev/null) gcloud logging read "resource.type=cloud_run_revision AND severity>=ERROR" \ --project="$PROJECT" --limit=20 --format="value(textPayload)" 2>/dev/null || true fiaws logs tail; Vercel:vercel logs; or the project's configured log viewer). Skip if not a production issue.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 269 lines · 46 tokens per session scan A 71ad6fd18063
issue is a skill published in the GitHub repository rajitsaha/100xprism (10 stars, last pushed 6d ago), licensed MIT. It adds 46 tokens to every session and 2,494 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.
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